Inter-individual variability in structural brain development from late childhood to young adulthood

Sources and components of fine air pollution exposure and brain morphology in preadolescents

Air pollution is an emerging novel neurotoxicant during childhood and adolescence. However, little is known regarding how fine particulate matter (PM2.5) components and its sources impact brain morphology. We investigated air pollution exposure-related differences in brain morphology using cross-sectional magnetic resonance imaging data from 10,095 children ages 9-11 years-old enrolled in the United States' Adolescent Brain Cognitive Development Study [2016-2018]. Air pollution estimates included fifteen PM2.5 constituent chemicals and metals, and six major sources of PM2.5 (e.g., crustal materials, biomass burning, traffic) identified from prior source apportionment, as well as nitrogen dioxide (NO2) and ozone (O3). After adjusting for demographic, socioeconomic, and neuroimaging covariates, we used partial least squares analyses to identify associations between simultaneous co-exposures and morphological differences in cortical thickness, surface area, and subcortical volumes. We found that greater exposure to PM2.5 and NO2 was associated with decreases in frontal and increases in inferior temporal surface area. PM2.5 component and source analyses linked cortical surface area and thickness to biomass burning (e.g., organic carbon, potassium), crustal material (e.g., calcium, silicon), and traffic (e.g., copper, iron) exposures, while smaller subcortical volumes were linked to greater potassium exposure. This is the first study to show differential effects of several air pollution sources on development of children's brains. Significant associations were found in brain structures involved in several cognitive and social processes, including lower- and higher-order sensory processing, socioemotional behaviors, and executive functioning. These findings highlight differential effects of several air pollution sources on brain structure in preadolescents across the U.S.

Nested hierarchical group-wise registration with a graph-based subgrouping strategy for efficient template construction

Accurate and efficient group-wise registration for medical images is fundamentally important to construct a common template image for population-level analysis. However, current group-wise registration faces the challenges posed by the algorithm's efficiency and capacity, and adaptability to large variations in the subject populations. This paper addresses these challenges with a novel Nested Hierarchical Group-wise Registration (NHGR) framework. Firstly, to alleviate the registration burden due to significant population variations, a new subgrouping strategy is proposed to serve as a "divide and conquer" mechanism that divides a large population into smaller subgroups. The subgroups with a hierarchical sequence are formed by gradually expanding the scale factors that relate to feature similarity and then conducting registration at the subgroup scale as the multi-scale conquer strategy. Secondly, the nested hierarchical group-wise registration is proposed to conquer the challenges due to the efficiency and capacity of the model from three perspectives. (1) Population level: the global group-wise registration is performed to generate age-related sub-templates from local subgroups progressively to the global population. (2) Subgroup level: the local group-wise registration is performed based on local image distributions to reduce registration error and achieve rapid optimization of sub-templates. (3) Image pair level: a deep multi-resolution registration network is employed for better registration efficiency. The proposed framework was evaluated on the brain datasets of adults and adolescents, respectively from 18 to 96 years and 5 to 21 years. Experimental results consistently demonstrated that our proposed group-wise registration method achieved better performance in terms of registration efficiency, template sharpness, and template centrality.

Multimodal Brain Age Indicators of Internalizing Problems in Early Adolescence: A Longitudinal Investigation

BACKGROUND

Adolescence is a time of increased risk for the onset of internalizing problems, particularly in females. However, how individual differences in brain maturation are related to the increased vulnerability for internalizing problems in adolescence remains poorly understood due to a scarcity of longitudinal studies.

METHODS

Using ABCD (Adolescent Brain Cognitive Development) Study data, we examined longitudinal associations between multimodal brain age and youth internalizing problems. Brain age models were trained, validated, and tested independently on T1-weighted imaging (n = 9523), diffusion tensor imaging (n = 8834), and resting-state functional magnetic resonance imaging (n = 8233) data at baseline (meanage = 9.9 years) and 2-year follow-up (meanage = 11.9 years). Self-reported internalizing problems were measured at 3-year follow-up (meanage = 12.9 years) using the Brief Problem Monitor.

RESULTS

Latent change score models demonstrated that although brain age gap (BAG) at baseline was not related to later internalizing problems, an increase in BAG between time points was positively associated with internalizing problems at 3-year follow-up in females but not males. This association between an increasing BAG and higher internalizing problems was observed in the T1-weighted imaging (β = 0.067, SE = 0.050, false discovery rate [FDR]-corrected p = .020) and resting-state functional magnetic resonance imaging (β = 0.090, SE = 0.025, pFDR = .007) models but not diffusion tensor imaging (β = -0.002, SE = 0.053, pFDR = .932) and remained significant when accounting for earlier internalizing problems.

CONCLUSIONS

A greater increase in BAG in early adolescence may reflect the heightened vulnerability shown by female youth to internalizing problems. Longitudinal research is necessary to understand whether this increasing BAG signifies accelerated brain development and its relationship to the trajectory of internalizing problems throughout adolescence.

Adolescent Vulnerability to Internet Media Exposure: The Role of Self-Mastery in Mitigating Post-Traumatic Symptoms

The internet has revolutionized communication, becoming central to daily life. Consequently, news consumption shifted dramatically with increased media access, exposing individuals to global traumatic events, such as armed conflicts. Adolescents are particularly vulnerable to the negative effects of this exposure due to their media expertise and developmental stage. Young adults are more mature and independent but remain vulnerable to the harmful effects of internet exposure. This study examined the relationship between internet media exposure to armed conflict and post-traumatic symptoms and psychiatric symptomology among adolescents and young adults. Additionally, self-mastery was explored as a resilience factor in both groups. A sample of 329 participants, including 159 adolescents (ages 12-18) and 168 young adults (ages 20-26), completed questionnaires assessing direct and internet media exposure to armed conflict events, self-mastery, post-traumatic symptoms and psychiatric symptomology. Structural equation modeling (SEM) revealed that internet media exposure was positively associated with post-traumatic symptoms and psychiatric symptomatology only among adolescents, whereas direct exposure was significantly related to post-traumatic symptoms only among young adults. Self-mastery moderated these effects in both groups, buffering the psychological impact of the most relevant exposure. The findings underscore the need for interventions that foster self-mastery to mitigate the adverse effects of traumatic media exposure, particularly among adolescents. Developmental implications are discussed.

A longitudinal neuroimaging study of adolescent girls' mentalizing and perspective-taking tendencies

Research in developmental psychology suggests that self-concept formation and mentalizing capacities, along with their neural foundations, show significant developmental change during adolescence. Perspective-taking tendencies are also believed to increase in adolescence, supporting the refinement of prosocial behavior and the demands of increasingly complex social relationships. To explore the development of, and relationship between, these processes in adolescence, early adolescent girls (N = 172) completed a measure of perspective-taking tendencies and a self-evaluation fMRI task at two waves, approximately 18 months apart (mean ages = 11.62 and 13.20, respectively). In line with our hypothesis, perspective-taking tendencies were positively associated with age. Greater perspective-taking tendencies were also associated with a more prosocial, and less antisocial, self-concept. In addition, dmPFC activity increased with age, but this did not survive correction for multiple comparisons across all mentalizing regions. Post hoc analyses also showed that an increase in perspective-taking tendencies across waves was significantly associated with activity in parts of the precuneus at wave 2. Finally, while we did not observe cross-variable coupling, our Bivariate Latent Change Score model showed that lower perspective-taking tendencies at wave 1 were associated with greater latent change in this variable (and the same was true for mean activity in mentalizing brain regions).

Longitudinal Sex-at-Birth and Age Analyses of Cortical Structure in the ABCD Study

While the brain continues to develop during adolescence, such development may depend on sex-at-birth. However, the elucidation of such differences may be hindered by analytical decisions (e.g., covariate selection to address brain-size differences) and the typical reporting of cross-sectional data. To further evaluate adolescent cortical development, we analyzed data from the Adolescent Brain Cognitive Development Study, whose cohort of 11,000+ youth participants with biannual neuroimaging data collection can facilitate understanding neuroanatomical change during a critical developmental window. Doubly considering individual differences within the context of group-level effects, we analyzed regional changes in cortical thickness, sulcal depth, surface area, and volume between two timepoints (∼2 years apart) in 9- to 12-year-olds assigned male or female sex-at-birth. First, we conducted linear mixed-effect models to gauge how controlling for intracranial volume, whole-brain volume (WBV), or a summary metric (e.g., mean cortical thickness) influenced interpretations of age-dependent cortical change. Next, we evaluated the relative changes in thickness and surface area as a function of sex-at-birth and age. Here, we showed that WBV (thickness, sulcal depth, volume) and total cortical surface area were more optimal covariates; controlling for different covariates would have substantially altered our interpretations of overall and sex-at-birth-specific neuroanatomical development. Furthermore, we provided evidence to suggest that aggregate change in how cortical thickness is changing relative to surface area is generally comparable across those assigned male or female sex-at-birth, with corresponding change happening at slightly older ages in those assigned male sex-at-birth. Overall, these results help elucidate neuroanatomical developmental trajectories in early adolescence.

Measuring and interpreting individual differences in fetal, infant, and toddler neurodevelopment

As scientists interested in fetal, infant, and toddler (FIT) neurodevelopment, our research questions often focus on how individual children differ in their neurodevelopment and the predictive value of those individual differences for long-term neural and behavioral outcomes. Measuring and interpreting individual differences in neurodevelopment can present challenges: Is there a "standard" way for the human brain to develop? How do the semantic, practical, or theoretical constraints that we place on studying "development" influence how we measure and interpret individual differences? While it is important to consider these questions across the lifespan, they are particularly relevant for conducting and interpreting research on individual differences in fetal, infant, and toddler neurodevelopment due to the rapid, profound, and heterogeneous changes happening during this period, which may be predictive of long-term outcomes. This article, therefore, has three goals: 1) to provide an overview about how individual differences in neurodevelopment are studied in the field of developmental cognitive neuroscience, 2) to identify challenges and considerations when studying individual differences in neurodevelopment, and 3) to discuss potential implications and solutions moving forward.

Preparing adolescents and young adults with epilepsy for transitioning health care (PATH) study: The important role of age and self-efficacy

BACKGROUND

At least 30% of youth with epilepsy will require transition from pediatric to adult neurology care. Many adolescents and young adults (AYAs) with epilepsy are inadequately prepared for health care transition, which may contribute to health care disruptions and decreased quality of life. The current study aimed to add to the growing body of literature on health care transition in epilepsy by characterizing a sample of AYAs with epilepsy and assessing the relationship between pre-existing and behaviorally modifiable factors and epilepsy-specific transition readiness.

METHODS

103 AYAs (Mage = 17.56; range = 14-21; 54% female; 85% White) with epilepsy and 84 of their caregivers were enrolled from two pediatric hospitals in the United States. Participants provided sociodemographic and medical information and completed questionnaires assessing functioning, epilepsy management, and transition readiness. Data were analyzed using a two-step hierarchical multiple linear regression model with epilepsy-specific transition readiness as the outcome: 1) pre-existing factors (i.e., age, insurance, seizure severity); and 2) behaviorally modifiable factors (i.e., cognitive functioning, medication self-management, epilepsy self-efficacy).

RESULTS

Only 44% of AYAs had discussed health care transition with their pediatric neurologist. The final model was significant, ΔF (3, 90) = 13.45, p < 0.001. Older age and greater epilepsy self-efficacy were associated with greater epilepsy-specific transition readiness.

CONCLUSION

AYAs with greater epilepsy self-efficacy may be better prepared for the transition from pediatric to adult neurology care. Routine assessment of epilepsy self-efficacy and transition readiness starting in early adolescence may help to identify individuals who could benefit from targeted interventions.

Multimodal neural correlates of childhood psychopathology

Complex structural and functional changes occurring in typical and atypical development necessitate multidimensional approaches to better understand the risk of developing psychopathology. Here, we simultaneously examined structural and functional brain network patterns in relation to dimensions of psychopathology in the Adolescent Brain Cognitive Development (ABCD) dataset. Several components were identified, recapitulating the psychopathology hierarchy, with the general psychopathology (p) factor explaining most covariance with multimodal imaging features, while the internalizing, externalizing, and neurodevelopmental dimensions were each associated with distinct morphological and functional connectivity signatures. Connectivity signatures associated with the p factor and neurodevelopmental dimensions followed the sensory-to-transmodal axis of cortical organization, which is related to the emergence of complex cognition and risk for psychopathology. Results were consistent in two separate data subsamples and robust to variations in analytical parameters. Although model parameters yielded statistically significant brain-behavior associations in unseen data, generalizability of the model was rather limited for all three latent components (r change from within- to out-of-sample statistics: LC1within = 0.36, LC1out = 0.03; LC2within = 0.34, LC2out = 0.05; LC3within = 0.35, LC3out = 0.07). Our findings help in better understanding biological mechanisms underpinning dimensions of psychopathology, and could provide brain-based vulnerability markers.

Development of Self-Concept in Childhood and Adolescence: How Neuroscience Can Inform Theory and Vice Versa

How do we develop a stable and coherent self-concept in contemporary times? Susan Harter's original work, The Construction of Self (1999; 2012), argues that cognitive and social processes are building blocks for developing a coherent sense of self, resulting in self-concept clarity across various domains in life (e.g., [pro-]social, academic, and physical). Here, we show how this framework guides and can benefit from recent findings on (1) the prolonged and nonlinear structural brain development during childhood and adolescence, (2) insights from developmental neuroimaging studies using self-concept appraisal paradigms, (3) genetic and environmental influences on behavioral and neural correlates of self-concept development, and (4) youth's perspectives on self-concept development in the context of 21st century global challenges. We examine how neuroscience can inform theory by testing several compelling questions related to stability versus change of neural, behavioral, and self-report measures and we reflect on the meaning of variability and change/growth.

Ventral striatal-cingulate resting-state functional connectivity in healthy adolescents relates to later depression symptoms in adulthood

BACKGROUND

Depression is a significant public health concern. Identifying biopsychosocial risk factors for depression is important for developing targeted prevention. Studies have demonstrated that blunted striatal activation during reward processing is a risk factor for depression; however, few have prospectively examined whether adolescent reward-related resting-state functional connectivity (rsFC) predicts depression symptoms in adulthood and how this relates to known risk factors (e.g., childhood trauma).

METHODS

At baseline, 66 adolescents (mean age = 14.7, SD = 1.4, 68 % female) underwent rsFC magnetic resonance imaging and completed the Children's Depression Inventory (CDI). At follow-up (mean time between adolescent scan and adult follow-up = 10.1 years, SD = 1.6, mean adult age = 24.8 years, SD = 1.7), participants completed the Childhood Trauma Questionnaire (CTQ) and Beck Depression Inventory- Second Edition (BDI-2). Average rsFC was calculated between nodes in mesocorticolimbic reward circuitry: ventral striatum (VS), rostral anterior cingulate cortex (rACC), medial orbitofrontal cortex, and ventral tegmental area. Linear regressions assessed associations between rsFC, BDI-2, and CTQ, controlling for adolescent CDI, sex assigned at birth, and scan age (Bonferroni corrected).

RESULTS

Greater childhood trauma was associated with higher adulthood depression symptoms. Stronger VS-rACC rsFC during adolescence was associated with greater depression symptoms in adulthood and greater childhood trauma.

LIMITATIONS

The small sample size, limited depression severity, and seed-based approach are limitations.

CONCLUSIONS

The associations between adolescent striatal-cingulate rsFC and childhood trauma and adult depression symptoms suggest this connectivity may be an early neurobiological risk factor for depression and that early life experience plays an important role. Increased VS-rACC connectivity may represent an over-regulatory response on the striatum, commonly reported in depression, and warrants further investigation.

The Dynamic Interplay Between Puberty and Structural Brain Development as a Predictor of Mental Health Difficulties in Adolescence: A Systematic Review

Puberty is a time of intense reorganization of brain structure and a high-risk period for the onset of mental health problems, with variations in pubertal timing and tempo intensifying this risk. We conducted 2 systematic reviews of articles published up to February 1, 2024, focusing on 1) the role of brain structure in the relationship between puberty and mental health, and 2) precision psychiatry research evaluating the utility of puberty in making individualized predictions of mental health outcomes in young people. The first review provides inconsistent evidence about whether and how pubertal and psychopathological processes may interact in relation to brain development. While most studies found an association between early puberty and mental health difficulties in adolescents, evidence on whether brain structure mediates this relationship is mixed. The pituitary gland was found to be associated with mental health status during this time, possibly through its central role in regulating puberty and its function in the hypothalamic-pituitary-gonadal and hypothalamic-pituitary-adrenal axes. In the second review, the design of studies that have explored puberty in predictive models did not allow for a quantification of its predictive power. However, when puberty was evaluated through physically observable characteristics rather than hormonal measures, it was more commonly identified as a predictor of depression, anxiety, and suicidality in adolescence. Social processes may be more relevant than biological ones to the link between puberty and mental health problems and represent an important target for educational strategies.

Integration of estimated regional gene expression with neuroimaging and clinical phenotypes at biobank scale

An understanding of human brain individuality requires the integration of data on brain organization across people and brain regions, molecular and systems scales, as well as healthy and clinical states. Here, we help advance this understanding by leveraging methods from computational genomics to integrate large-scale genomic, transcriptomic, neuroimaging, and electronic-health record data sets. We estimated genetically regulated gene expression (gr-expression) of 18,647 genes, across 10 cortical and subcortical regions of 45,549 people from the UK Biobank. First, we showed that patterns of estimated gr-expression reflect known genetic-ancestry relationships, regional identities, as well as inter-regional correlation structure of directly assayed gene expression. Second, we performed transcriptome-wide association studies (TWAS) to discover 1,065 associations between individual variation in gr-expression and gray-matter volumes across people and brain regions. We benchmarked these associations against results from genome-wide association studies (GWAS) of the same sample and found hundreds of novel associations relative to these GWAS. Third, we integrated our results with clinical associations of gr-expression from the Vanderbilt Biobank. This integration allowed us to link genes, via gr-expression, to neuroimaging and clinical phenotypes. Fourth, we identified associations of polygenic gr-expression with structural and functional MRI phenotypes in the Human Connectome Project (HCP), a small neuroimaging-genomic data set with high-quality functional imaging data. Finally, we showed that estimates of gr-expression and magnitudes of TWAS were generally replicable and that the p-values of TWAS were replicable in large samples. Collectively, our results provide a powerful new resource for integrating gr-expression with population genetics of brain organization and disease.

Pterion variation in the skulls of rhesus macaques from Cayo Santiago: Inheritance, development, and pathology

The pterion is the sutural juncture of the frontal, parietal, sphenoidal, temporal, and zygomatic bones on the lateral aspect of the cranium. As a craniometric landmark, the pterion has a taxonomic valence, in addition to a common neurosurgical entry point in medicine. Variation in the articulation patterns at the pterion have been documented between primate species yet have a high degree of uniformity within species, suggesting a genetic control for this complex region of the skull. In this study, pterion pattern variation was investigated in 1627 Rhesus macaque crania of the Cayo Santiago colony. The colony's associated skeletal collections accompany known age, sex, and maternal lineages. Pterion pattern prevalence rates were tested against matrilines, as well as cranial shape, and cranial sutural fusion ages (including individuals with prematurely fused sutures). Five patterns were identified, the most prominent being the prevailing Old World Monkey frontotemporal (FT) articulation (83.4%). The relative frequency of those not exhibiting the FT pattern was found to vary considerably between matrilineal families (p = 0.037), ranging from 5.3% to 34.2%. Mothers with the non-FT pterion pattern were three times as likely to bear non-FT offspring. Cranial shape additionally varied with pterion type. Males exhibiting zygomaticotemporal (ZT) and sphenoparietal (SP) articulations possessed a relatively longer and narrower cranium than those with the default FT type (p = < 0.001). Cranial sutural fusion ages were not found to differ between pterion types, though all individuals with craniosynostosis (6; 0.38%) exhibited the FT type. The study provided strong evidence for a genetic source for pterion pattern as well as outlining a relatively novel relationship with cranial shape and sutural fusion ages. A unifying explanation may lie in those genes involved in both sutural and craniofacial development, or in the variation of brain growth processes channeling sutural articulation at the pterion. Both may be heritable and responsible for producing observed matrilineal differences in the pterion.

Longitudinal mapping of cortical change during early adolescence associated with prenatal tobacco and/or alcohol exposure in the Adolescent Brain Cognitive Development Study

Importance

The effects of prenatal alcohol (PAE) and tobacco exposure (PTE) on adolescent neuroanatomical development are typically evaluated cross-sectionally. It is unclear if observed effects persist throughout life or reflect different developmental trajectories.

Objective

To determine how PAE and PTE are associated with cortical structure and development across two timepoints in early adolescence.

Design

Observational, longitudinal analyses of data within the Adolescent Brain Cognitive Development Study.

Setting

21 study sites in the United States.

Participants

5,417 youth participants, aged ~9-12 years old.

Exposures

PAE and PTE based on caregiver (self) reports of alcohol/tobacco use during pregnancy, before and after pregnancy recognition.

Main Outcomes and Measures

Cortical thickness (mm) and cortical surface area (mm2) measured approximately 2 years apart in early adolescence, across 68 bilateral cortical regions.

Results

At baseline data collection, youth participants were ~9.9 years old (SD=0.6). At the second neuroimaging appointment, youth participants were ~11.9 years old (SD=0.6). When modelling cortical thickness, we controlled for individuals' whole-brain volume; when modelling cortical surface area, individuals' total surface area. Cortical thickness generally declined with age. Cortical surface area either expanded or contracted with age, depending on region. PAE had minimal effects on cortical structure (main effects) and development (PAE×Age interactions). PTE had robust effects on cortical thickness and was associated with faster rates of cortical thinning in several regions within the frontal lobe. Post hoc analyses on (1) the effects of PTE for those who continued tobacco use after pregnancy recognition and (2) the effects of PTE in those who did not also use alcohol revealed weaker effects.

Conclusions and Relevance

PTE had robust effects on neuroanatomical structure and longitudinal development, particularly cortical thickness. Analyzing developmental cortical trajectories informs how PTE and/or PAE not only affects cortical structure but how it develops long after those prenatal exposures occurred. Future analyses involving cotinine biomarkers of PTE would enhance the temporal resolution of the ABCD Study®'s PTE-related queries of tobacco use before and after learning of the pregnancy.

MULTIMODAL NEURAL CORRELATES OF CHILDHOOD PSYCHOPATHOLOGY

Complex structural and functional changes occurring in typical and atypical development necessitate multidimensional approaches to better understand the risk of developing psychopathology. Here, we simultaneously examined structural and functional brain network patterns in relation to dimensions of psychopathology in the Adolescent Brain Cognitive Development dataset. Several components were identified, recapitulating the psychopathology hierarchy, with the general psychopathology (p) factor explaining most covariance with multimodal imaging features, while the internalizing, externalizing, and neurodevelopmental dimensions were each associated with distinct morphological and functional connectivity signatures. Connectivity signatures associated with the p factor and neurodevelopmental dimensions followed the sensory-to-transmodal axis of cortical organization, which is related to the emergence of complex cognition and risk for psychopathology. Results were consistent in two separate data subsamples, supporting generalizability, and robust to variations in analytical parameters. Our findings help in better understanding biological mechanisms underpinning dimensions of psychopathology, and could provide brain-based vulnerability markers.

Genetic and environmental influences on structural brain development from childhood to adolescence: A longitudinal twin study on cortical thickness, surface area, and subcortical volume

The human brain undergoes structural development from childhood to adolescence, with specific regions in the sensorimotor, social, and affective networks continuing to grow into adulthood. While genetic and environmental factors contribute to individual differences in these brain trajectories, the extent remains understudied. Our longitudinal study, utilizing up to three biennial MRI scans (n=485), aimed to assess the genetic and environmental effects on brain structure (age 7) and development (ages 7-14) in these regions. Heritability estimates varied across brain regions, with all regions showing genetic influence (ranging from 18 % to 59 %) with additional shared environmental factors affecting the primary motor cortex (30 %), somatosensory cortex (35 %), DLPFC (5 %), TPJ (17 %), STS (17 %), precuneus (10 %), hippocampus (22 %), amygdala (5 %), and nucleus accumbens (10 %). Surface area was more genetically driven (38 %) than cortical thickness (14 %). Longitudinal brain changes were primarily driven by genetics (ranging from 1 % to 29 %), though shared environment factors (additionally) influenced the somatosensory cortex (11 %), DLPFC (7 %), cerebellum (28 %), TPJ (16 %), STS (20 %), and hippocampus (17 %). These findings highlight the importance of further investigating brain-behavior associations and the influence of enriched and deprived environments from childhood to adolescence. Ultimately, our study can provide insights for interventions aimed at supporting children's development.

Investigating grey matter volumetric trajectories through the lifespan at the individual level

Adolescents exhibit remarkable heterogeneity in the structural architecture of brain development. However, due to limited large-scale longitudinal neuroimaging studies, existing research has largely focused on population averages, and the neurobiological basis underlying individual heterogeneity remains poorly understood. Here we identify, using the IMAGEN adolescent cohort followed up over 9 years (14-23 y), three groups of adolescents characterized by distinct developmental patterns of whole-brain gray matter volume (GMV). Group 1 show continuously decreasing GMV associated with higher neurocognitive performances than the other two groups during adolescence. Group 2 exhibit a slower rate of GMV decrease and lower neurocognitive performances compared with Group 1, which was associated with epigenetic differences and greater environmental burden. Group 3 show increasing GMV and lower baseline neurocognitive performances due to a genetic variation. Using the UK Biobank, we show these differences may be attenuated in mid-to-late adulthood. Our study reveals clusters of adolescent neurodevelopment based on GMV and the potential long-term impact.

The effect of intrathecal recombinant arylsulfatase A therapy on structural brain magnetic resonance imaging in children with metachromatic leukodystrophy

This study aimed to evaluate the effect of intrathecal (IT) recombinant human arylsulfatase A (rhASA) on magnetic resonance imaging (MRI)-assessed brain tissue changes in children with metachromatic leukodystrophy (MLD). In total, 510 MRI scans were collected from 12 intravenous (IV) rhASA-treated children with MLD, 24 IT rhASA-treated children with MLD, 32 children with untreated MLD, and 156 normally developing children. Linear mixed models were fitted to analyze the time courses of gray matter (GM) volume and fractional anisotropy (FA) in the posterior limb of the internal capsule. Time courses for demyelination load and FA in the centrum semiovale were visualized using locally estimated scatterplot smoothing regression curves. All assessed imaging parameters demonstrated structural evidence of neurological deterioration in children with MLD. GM volume was significantly lower at follow-up (median duration, 104 weeks) in IV rhASA-treated versus IT rhASA-treated children. GM volume decline over time was steeper in children receiving low-dose (10 or 30 mg) versus high-dose (100 mg) IT rhASA. Similar effects were observed for demyelination. FA in the posterior limb of the internal capsule showed a higher trend over time in IT rhASA-treated versus children with untreated MLD, but FA parameters were not different between children receiving the low doses versus those receiving the high dose. GM volume in IT rhASA-treated children showed a strong positive correlation with 88-item Gross Motor Function Measure score over time. In some children with MLD, IT administration of high-dose rhASA may delay neurological deterioration (assessed using MRI), offering potential therapeutic benefit.

Spatiotemporal patterns in cortical development: Age, puberty, and individual variability from 9 to 13 years of age

Humans and nonhuman primate studies suggest that timing and tempo of cortical development varies neuroanatomically along a sensorimotor-to-association (S-A) axis. Prior human studies have reported a principal S-A axis across various modalities, but largely rely on cross-sectional samples with wide age-ranges. Here, we investigate developmental changes and individual variability in cortical organization along the S-A axis between the ages of 9-13 years using a large, longitudinal sample (N = 2487-3747, 46-50% female) from the Adolescent Brain Cognitive Development Study (ABCD Study®). This work assesses multiple aspects of neurodevelopment indexed by changes in cortical thickness, cortical microarchitecture, and resting-state functional fluctuations. First, we evaluated S-A organization in age-related changes and, then, computed individual-level S-A alignment in brain changes and assessing differences therein due to age, sex, and puberty. Varying degrees of linear and quadratic age-related brain changes were identified along the S-A axis. Yet, these patterns of cortical development were overshadowed by considerable individual variability in S-A alignment. Even within individuals, there was little correspondence between S-A patterning across the different aspects of neurodevelopment investigated (i.e., cortical morphology, microarchitecture, function). Some of the individual variation in developmental patterning of cortical morphology and microarchitecture was explained by age, sex, and pubertal development. Altogether, this work contextualizes prior findings that regional age differences do progress along an S-A axis at a group level, while highlighting broad variation in developmental change between individuals and between aspects of cortical development, in part due to sex and puberty.

Significance Statement

Understanding normative patterns of adolescent brain change, and individual variability therein, is crucial for disentangling healthy and abnormal development. We used longitudinal human neuroimaging data to study several aspects of neurodevelopment during early adolescence and assessed their organization along a sensorimotor-to-association (S-A) axis across the cerebral cortex. Age differences in brain changes were linear and curvilinear along this S-A axis. However, individual-level sensorimotor-association alignment varied considerably, driven in part by differences in age, sex, and pubertal development.

Altered morphometric similarity networks in insomnia disorder

Previous studies on structural covariance network (SCN) suggested that patients with insomnia disorder (ID) show abnormal structural connectivity, primarily affecting the somatomotor network (SMN) and default mode network (DMN). However, evaluating a single structural index in SCN can only reveal direct covariance relationship between two brain regions, failing to uncover synergistic changes in multiple structural features. To cover this research gap, the present study utilized novel morphometric similarity networks (MSN) to examine the morphometric similarity between cortical areas in terms of multiple sMRI parameters measured at each area. With seven T1-weighted imaging morphometric features from the Desikan-Killiany atlas, individual MSN was constructed for patients with ID (N = 87) and healthy control groups (HCs, N = 84). Two-sample t-test revealed differences in MSN between patients with ID and HCs. Correlation analyses examined associations between MSNs and sleep quality, insomnia symptom severity, and depressive symptoms severity in patients with ID. The right paracentral lobule (PCL) exhibited decreased morphometric similarity in patients with ID compared to HCs, mainly manifested by its de-differentiation (meaning loss of distinctiveness) with the SMN, DMN, and ventral attention network (VAN), as well as its decoupling with the visual network (VN). Greater PCL-based de-differentiation correlated with less severe insomnia and fewer depressive symptoms in the patients group. Additionally, patients with less depressive symptoms showed greater PCL de-differentiation from the SMN. As an important pilot step in revealing the underlying morphometric similarity alterations in insomnia disorder, the present study identified the right PCL as a hub region that is de-differentiated with other high-order networks. Our study also revealed that MSN has an important potential to capture clinical significance related to insomnia disorder.

Air pollution from biomass burning disrupts early adolescent cortical microarchitecture development

Exposure to outdoor particulate matter (PM2.5) represents a ubiquitous threat to human health, and particularly the neurotoxic effects of PM2.5 from multiple sources may disrupt neurodevelopment. Studies addressing neurodevelopmental implications of PM exposure have been limited by small, geographically limited samples and largely focus either on macroscale cortical morphology or postmortem histological staining and total PM mass. Here, we leverage residentially assigned exposure to six, data-driven sources of PM2.5 and neuroimaging data from the longitudinal Adolescent Brain Cognitive Development Study (ABCD Study®), collected from 21 different recruitment sites across the United States. To contribute an interpretable and actionable assessment of the role of air pollution in the developing brain, we identified alterations in cortical microstructure development associated with exposure to specific sources of PM2.5 using multivariate, partial least squares analyses. Specifically, average annual exposure (i.e., at ages 8-10 years) to PM2.5 from biomass burning was related to differences in neurite development across the cortex between 9 and 13 years of age.

Why and how to collect representative study samples in educational neuroscience research

BACKGROUND

Educational neuroscience research, which investigates the neurobiological mechanisms of learning, has historically incorporated samples drawn mostly from white, middle-class, and/or suburban populations. However, sampling in research without attending to representation can lead to biased interpretations and results that are less generalizable to an intended target population. Prior research revealing differences in neurocognitive outcomes both within- and across-groups further suggests that such practices may obscure significant effects with practical implications.

BARRIERS

Negative attitudes among historically marginalized communities, stemming from historical mistreatment, biased research outcomes, and implicit or explicit attitudes among research teams, can hinder diverse participation. Qualities of the research process including language requirements, study locations, and time demands create additional barriers.

SOLUTIONS

Flexible data collection approaches, community engaugement, and transparent reporting could build trust and enhance sampling diversity. Longer-term solutions include prioritizing research questions relevant to marginalized communities, increasing workforce diversity, and detailed reporting of sample demographics. Such concerted efforts are essential for robust educational neuroscience research to maximize positive impacts broadly across learners.

Navigating Pubertal Goldilocks: The Optimal Pace for Hierarchical Brain Organization

Adolescence is a timed process with an onset, tempo, and duration. Nevertheless, the temporal dimension, especially the pace of maturation, remains an insufficiently studied aspect of developmental progression. The primary objective is to estimate the precise influence of pubertal maturational tempo on the configuration of associative brain regions. To this end, the connection between maturational stages and the level of hierarchical organization of large-scale brain networks in 12-13-year-old females is analyzed. Skeletal maturity is used as a proxy for pubertal progress. The degree of maturity is defined by the difference between bone age and chronological age. To assess the level of hierarchical organization in the brain, the temporal dynamic of closed eye resting state high-density electroencephalography (EEG) in the alpha frequency range is analyzed. Different levels of hierarchical order are captured by the measured asymmetry in the directionality of information flow between different regions. The calculated EEG-based entropy production of participant groups is then compared with accelerated, average, and decelerated maturity. Results indicate that an average maturational trajectory optimally aligns with cerebral hierarchical order, and both accelerated and decelerated timelines result in diminished cortical organization. This suggests that a "Goldilocks rule" of brain development is favoring a particular maturational tempo.

Cortical thickness and grey-matter volume anomaly detection in individual MRI scans: Comparison of two methods

Over the past decades, morphometric analysis of brain MRI has contributed substantially to the understanding of healthy brain structure, development and aging as well as to improved characterisation of disease related pathologies. Certified commercial tools based on normative modeling of these metrics are meanwhile available for diagnostic purposes, but they are cost intensive and their clinical evaluation is still in its infancy. Here we have compared the performance of "ScanOMetrics", an open-source research-level tool for detection of statistical anomalies in individual MRI scans, depending on whether it is operated on the output of FreeSurfer or of the deep learning based brain morphometry tool DL + DiReCT. When applied to the public OASIS3 dataset, containing patients with Alzheimer's disease (AD) and healthy controls (HC), cortical thickness anomalies in patient scans were mainly detected in regions that are known as predilection areas of cortical atrophy in AD, regardless of the software used for extraction of the metrics. By contrast, anomaly detections in HCs were up to twenty-fold reduced and spatially unspecific using both DL + DiReCT and FreeSurfer. Progression of the atrophy pattern with clinical dementia rating (CDR) was clearly observable with both methods. DL + DiReCT provided results in less than 25 min, more than 15 times faster than FreeSurfer. This difference in computation time might be relevant when considering application of this or similar methodology as diagnostic decision support for neuroradiologists.

Air pollution from biomass burning disrupts early adolescent cortical microarchitecture development

Exposure to outdoor particulate matter (PM 2.5 ) represents a ubiquitous threat to human health, and particularly the neurotoxic effects of PM 2.5 from multiple sources may disrupt neurodevelopment. Studies addressing neurodevelopmental implications of PM exposure have been limited by small, geographically limited samples and largely focus either on macroscale cortical morphology or postmortem histological staining and total PM mass. Here, we leverage residentially assigned exposure to six, data-driven sources of PM 2.5 and neuroimaging data from the longitudinal Adolescent Brain Cognitive Development Study (ABCD Study®), collected from 21 different recruitment sites across the United States. To contribute an interpretable and actionable assessment of the role of air pollution in the developing brain, we identified alterations in cortical microstructure development associated with exposure to specific sources of PM 2.5 using multivariate, partial least squares analyses. Specifically, average annual exposure (i.e., at ages 8-10 years) to PM 2.5 from biomass burning was related to differences in neurite development across the cortex between 9 and 13 years of age.

Lost in between-the transition process from a child and adolescent eating disorder service to adult mental health services in the German health care system

INTRODUCTION

In young adults with anorexia nervosa (AN), the process of transition from a child and adolescent mental health service (CAMHS) to an adult mental health service (AMHS) has been recognized as critical, and many patients fear falling through the gap between the two types of service. As reports about the transition process in emerging adults with AN are scarce, the present study aimed to explore the problems and experiences of this age group.

METHOD

We screened our registry for patients with AN who had been treated as inpatients during childhood and/or adolescence and come of age during the last 3 years. Thirty-two female patients [mean age 20.3 (1.2) y.] agreed to participate in a semistructured personal or telephone interview assessing their demographic and clinical data, whether they had finalised the transition, and their wishes and experiences regarding the transition process.

RESULTS

Only approximately one-third of the participants had already undergone the transition. Nearly 60% of the former patients were still cared for by a CAMHS, and only 12.5% had stopped treatment for AN. Approximately 60% were exclusively or additionally cared for by their general practitioner. More than 50% of the participants still lived with their parents. Approximately 90% of the participants who remained in a CAMHS expressed concerns about transitioning, mostly about losing their trusted therapist and the assumption of personal responsibility.

CONCLUSION

Patients with AN often delay the transition from a CAMHS to an AMHS, which they experience as intimidating and overwhelming. Thus, patients should be better prepared for the transition, which should be linked to "developmental readiness" and not to chronological age. Because many patients still live with their family of origin, parents and their family physician should be closely involved in the transition process.

Comparing the multivariate relationships of conceptual adversity models and structural brain development in adolescent girls: A registered report

Adverse experiences throughout development confer risk for a multitude of negative long-term outcomes, but the processes via which these experiences are neurobiologically embedded are still unclear. Adolescence provides an opportunity to understand how these experiences impact the brain's rapidly changing structure. Two models are central to current adversity conceptualizations: a cumulative risk model, where all types of experiences are combined to represent accumulating stress, and a dimensional model, where certain features of experience (e.g., threat or deprivation) exert unique neurophysiological influence. In this registered report, we extended upon previous research by using a form of representational similarity analysis to examine whether the dimensional and cumulative risk models of adversity predict cortical thinning in frontoparietal and frontotemporal networks and volumetric changes in subcortical regions throughout adolescence. Drawing from a longitudinal sample of 179 adolescent girls (ages 10-13 years at the first wave) from Lane County, Oregon, United States, and up to four waves of follow-up data, we found that operationalizing adversity by similarity in threat and deprivation provided better prediction of brain development than similarity in overall adversity. However, these dimensions do not exhibit unique associations with developmental changes in the hypothesized brain changes. These results underscore the significance of carefully defining adversity and considering its impact on the entire brain. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Cortical growth from infancy to adolescence in preterm and term-born children

Early life experiences can exert a significant influence on cortical and cognitive development. Very preterm birth exposes infants to several adverse environmental factors during hospital admission, which affect cortical architecture. However, the subsequent consequence of very preterm birth on cortical growth from infancy to adolescence has never been defined; despite knowledge of critical periods during childhood for establishment of cortical networks. Our aims were to: chart typical longitudinal cortical development and sex differences in cortical development from birth to adolescence in healthy term-born children; estimate differences in cortical development between children born at term and very preterm; and estimate differences in cortical development between children with normal and impaired cognition in adolescence. This longitudinal cohort study included children born at term (≥37 weeks' gestation) and very preterm (<30 weeks' gestation) with MRI scans at ages 0, 7 and 13 years (n = 66 term-born participants comprising 34 with one scan, 18 with two scans and 14 with three scans; n = 201 very preterm participants comprising 56 with one scan, 88 with two scans and 57 with three scans). Cognitive assessments were performed at age 13 years. Cortical surface reconstruction and parcellation were performed with state-of-the-art, equivalent MRI analysis pipelines for all time points, resulting in longitudinal cortical volume, surface area and thickness measurements for 62 cortical regions. Developmental trajectories for each region were modelled in term-born children, contrasted between children born at term and very preterm, and contrasted between all children with normal and impaired cognition. In typically developing term-born children, we documented anticipated patterns of rapidly increasing cortical volume, area and thickness in early childhood, followed by more subtle changes in later childhood, with smaller cortical size in females than males. In contrast, children born very preterm exhibited increasingly reduced cortical volumes, relative to term-born children, particularly during ages 0-7 years in temporal cortical regions. This reduction in cortical volume in children born very preterm was largely driven by increasingly reduced cortical thickness rather than area. This resulted in amplified cortical volume and thickness reductions by age 13 years in individuals born very preterm. Alterations in cortical thickness development were found in children with impaired language and memory. This study shows that the neurobiological impact of very preterm birth on cortical growth is amplified from infancy to adolescence. These data further inform the long-lasting impact on cortical development from very preterm birth, providing broader insights into neurodevelopmental consequences of early life experiences.

Transitions from child and adolescent to adult mental health services for eating disorders: an in-depth systematic review and development of a transition framework

BACKGROUND

Eating disorders (EDs) peak in mid-to-late adolescence and often persist into adulthood. Given their early onset and chronicity, many patients transition from child and adolescent mental health services (CAMHS) to adult mental health services (AMHS) for ongoing, speciality ED care. This transition typically occurs at 18 years of age, when important biological, psychosocial, and vocational changes take place. Thus, smooth and effective transitions are paramount for ensuring service continuity, as well as reducing the risk of ED relapse and premature death. Here, we synthesized evidence on transitions from CAMHS to AMHS for young people with EDs, aiming to inform future research, clinical practice, and healthcare policy.

METHODS

A systematic review of the literature was conducted. This adhered to PRISMA guidelines. PubMed, Embase, and Scopus electronic databases were queried from inception to December 3, 2023. Leveraging the PICOS framework, study eligibility was evaluated in the qualitative synthesis. Data regarding methodology, analytic approach, and associated outcomes were then extracted. The quality of evidence was examined using critical appraisal tools. Finally, concept mapping was applied to organize findings into a transition framework.

RESULTS

The search returned 76 articles. Of these, 14 were included in the final review. Articles were grouped into 'qualitative' (n = 10), 'cross-sectional' (n = 2), and 'longitudinal cohort' (n = 2) studies based on research design. Overall, ED transitions were complex, multifaceted, and challenging for patients, caregivers, and providers alike. This resulted from an interplay of temporal- (e.g., timing of ED onset and transition), stakeholder- (e.g., patient ambivalence towards recovery) and systemic- (e.g., differences between services) related factors. Most studies were of moderate-to-high quality. Findings informed the development of five transition strategies designed to facilitate effective transfers across ED care: Timely talks, Readiness, Inclusion, Preparation, and Synergy (TRIPS).

CONCLUSIONS

Transitions from CAMHS to AMHS appear problematic for young people with EDs and other involved stakeholders. The field stands to benefit from TRIPS, an actionable, evidence-based framework that aims to alleviate challenges of transitioning and subsequently improve ED trajectories. As a logical next step, future work should empirically test the TRIPS framework, exploring its predictive utility and clinical value.

Recommendations for a Better Understanding of Sex and Gender in the Neuroscience of Mental Health

There are prominent sex/gender differences in the prevalence, expression, and life span course of mental health and neurodiverse conditions. However, the underlying sex- and gender-related mechanisms and their interactions are still not fully understood. This lack of knowledge has harmful consequences for those with mental health problems. Therefore, we set up a cocreation session in a 1-week workshop with a multidisciplinary team of 25 researchers, clinicians, and policy makers to identify the main barriers in sex and gender research in the neuroscience of mental health. Based on this work, here we provide recommendations for methodologies, translational research, and stakeholder involvement. These include guidelines for recording, reporting, analysis beyond binary groups, and open science. Improved understanding of sex- and gender-related mechanisms in neuroscience may benefit public health because this is an important step toward precision medicine and may function as an archetype for studying diversity.

Trial-level ERPs predicted behavioral responses during self-referential processing in late childhood

Self-referential information is uniquely salient and preferentially processed even in children. The literature has used the self-referent encoding task (SRET) combined with event-related potentials (ERPs) to study self-referential processing and its associations with youth psychopathology. However, it is unclear how the ERP and behavioral indices of SRET are associated with each other, although this knowledge can promote our mechanistic understanding of this construct and its role in psychopathology. We examined this question in 115 9- to 12-year-old children, a critical period for the development of self-related concepts. By applying a multilevel modeling approach to the trial-level data of SRET, we disaggregated the between- and within-person variability and observed within-person, but not between-person, effects of the P2 and late positive potential (LPP) on behavioral responses: a larger P2 on a given trial predicted a faster response in this trial; a larger LPP on a given trial predicted a higher likelihood of endorsing the word of this trial. We provided novel evidence on how the within-person variability of the ERPs predicted the overt responses of the SRET in children. These findings inform our mechanistic knowledge of self-referential processing and shed light on a better understanding of the role of self-referential processing in the development of psychopathology.

Adolescent to young adult longitudinal development of subcortical volumes in two European sites with four waves

Adolescent subcortical structural brain development might underlie psychopathological symptoms, which often emerge in adolescence. At the same time, sex differences exist in psychopathology, which might be mirrored in underlying sex differences in structural development. However, previous studies showed inconsistencies in subcortical trajectories and potential sex differences. Therefore, we aimed to investigate the subcortical structural trajectories and their sex differences across adolescence using for the first time a single cohort design, the same quality control procedure, software, and a general additive mixed modeling approach. We investigated two large European sites from ages 14 to 24 with 503 participants and 1408 total scans from France and Germany as part of the IMAGEN project including four waves of data acquisition. We found significantly larger volumes in males versus females in both sites and across all seven subcortical regions. Sex differences in age-related trajectories were observed across all regions in both sites. Our findings provide further evidence of sex differences in longitudinal adolescent brain development of subcortical regions and thus might eventually support the relationship of underlying brain development and different adolescent psychopathology in boys and girls.

Estimating cortical thickness trajectories in children across different scanners using transfer learning from normative models

This work illustrates the use of normative models in a longitudinal neuroimaging study of children aged 6-17 years and demonstrates how such models can be used to make meaningful comparisons in longitudinal studies, even when individuals are scanned with different scanners across successive study waves. More specifically, we first estimated a large-scale reference normative model using Hierarchical Bayesian Regression from N = 42,993 individuals across the lifespan and from dozens of sites. We then transfer these models to a longitudinal developmental cohort (N = 6285) with three measurement waves acquired on two different scanners that were unseen during estimation of the reference models. We show that the use of normative models provides individual deviation scores that are independent of scanner effects and efficiently accommodate inter-site variations. Moreover, we provide empirical evidence to guide the optimization of sample size for the transfer of prior knowledge about the distribution of regional cortical thicknesses. We show that a transfer set containing as few as 25 samples per site can lead to good performance metrics on the test set. Finally, we demonstrate the clinical utility of this approach by showing that deviation scores obtained from the transferred normative models are able to detect and chart morphological heterogeneity in individuals born preterm.

Genetic and brain similarity independently predict childhood anthropometrics and neighborhood socioeconomic conditions

Linking the developing brain with individual differences in clinical and demographic traits is challenging due to the substantial interindividual heterogeneity of brain anatomy and organization. Here we employ an integrative approach that parses individual differences in both cortical thickness and common genetic variants, and assess their effects on a wide set of childhood traits. The approach uses a linear mixed model framework to obtain the unique effects of each type of similarity, as well as their covariance. We employ this approach in a sample of 7760 unrelated children in the ABCD cohort baseline sample (mean age 9.9, 46.8% female). In general, associations between cortical thickness similarity and traits were limited to anthropometrics such as height, weight, and birth weight, as well as a marker of neighborhood socioeconomic conditions. Common genetic variants explained significant proportions of variance across nearly all included outcomes, although estimates were somewhat lower than previous reports. No significant covariance of the effects of genetic and cortical thickness similarity was found. The present findings highlight the connection between anthropometrics as well as neighborhood socioeconomic conditions and the developing brain, which appear to be independent from individual differences in common genetic variants in this population-based sample.

Assessing individual variability of the entorhinal subfields in health and disease

Investigating interindividual variability is a major field of interest in neuroscience. The entorhinal cortex (EC) is essential for memory and affected early in the progression of Alzheimer's disease (AD). We combined histology ground-truth data with ultrahigh-resolution 7T ex vivo MRI to analyze EC interindividual variability in 3D. Further, we characterized (1) entorhinal shape as a whole, (2) entorhinal subfield range and midpoints, and (3) subfield architectural location and tau burden derived from 3D probability maps. Our results indicated that EC shape varied but was not related to demographic or disease factors at this preclinical stage. The medial intermediate subfield showed the highest degree of location variability in the probability maps. However, individual subfields did not display the same level of variability across dimensions and outcome measure, each providing a different perspective. For example, the olfactory subfield showed low variability in midpoint location in the superior-inferior dimension but high variability in anterior-posterior, and the subfield entorhinal intermediate showed a large variability in volumetric measures but a low variability in location derived from the 3D probability maps. These findings suggest that interindividual variability within the entorhinal subfields requires a 3D approach incorporating multiple outcome measures. This study provides 3D probability maps of the individual entorhinal subfields and respective tau pathology in the preclinical stage (Braak I and II) of AD. These probability maps illustrate the subfield average and may serve as a checkpoint for future modeling.

From mother to child: How intergenerational transfer is reflected in similarity of corticolimbic brain structure and mental health

BACKGROUND

Intergenerational transfer effects include traits transmission from parent to child. While behaviorally well documented, studies on intergenerational transfer effects for brain structure or functioning are scarce, especially those examining relations of behavioral and neurobiological endophenotypes. This study aims to investigate behavioral and neural intergenerational transfer effects associated with the corticolimbic circuitry, relevant for socioemotional functioning and mental well-being.

METHODS

T1-neuroimaging and behavioral data was obtained from 72 participants (39 mother-child dyads/ 39 children; 7-13 years; 16 girls/ 33 mothers; 26-52 years). Gray matter volume (GMV) was extracted from corticolimbic regions (subcortical: amygdala, hippocampus, nucleus accumbens; neocortical: anterior cingulate, medial orbitofrontal areas). Mother-child similarity was quantified by correlation coefficients and comparisons to random adult-child pairs.

RESULTS

We identified significant corticolimbic mother-child similarity (r = 0.663) stronger for subcortical over neocortical regions. Mother-child similarity in mental well-being was significant (r = 0.409) and the degree of dyadic similarity in mental well-being was predicted by similarity in neocortical, but not subcortical GMV.

CONCLUSION

Intergenerational neuroimaging reveals significant mother-child transfer for corticolimbic GMV, most strongly for subcortical regions. However, variations in neocortical similarity predicted similarity in mother-child well-being. Ultimately, such techniques may enhance our knowledge of behavioral and neural familial transfer effects relevant for health and disease.

Prediction of brain age using structural magnetic resonance imaging: A comparison of accuracy and test-retest reliability of publicly available software packages

Brain age prediction algorithms using structural magnetic resonance imaging (MRI) aim to assess the biological age of the human brain. The difference between a person's chronological age and the estimated brain age is thought to reflect deviations from a normal aging trajectory, indicating a slower or accelerated biological aging process. Several pre-trained software packages for predicting brain age are publicly available. In this study, we perform a comparison of such packages with respect to (1) predictive accuracy, (2) test-retest reliability, and (3) the ability to track age progression over time. We evaluated the six brain age prediction packages: brainageR, DeepBrainNet, brainage, ENIGMA, pyment, and mccqrnn. The accuracy and test-retest reliability were assessed on MRI data from 372 healthy people aged between 18.4 and 86.2 years (mean 38.7 ± 17.5 years). All packages showed significant correlations between predicted brain age and chronological age (r = 0.66-0.97, p < 0.001), with pyment displaying the strongest correlation. The mean absolute error was between 3.56 (pyment) and 9.54 years (ENIGMA). brainageR, pyment, and mccqrnn were superior in terms of reliability (ICC values between 0.94-0.98), as well as predicting age progression over a longer time span. Of the six packages, pyment and brainageR consistently showed the highest accuracy and test-retest reliability.

Age related differences in symptom networks of overall psychological functioning in a sample of patients diagnosed with anxiety, obsessive compulsive disorder, or posttraumatic stress disorder

Anxiety disorders, obsessive compulsive disorder (OCD), and posttraumatic stress disorder (PTSD) are among the most prevalent mental disorders across the lifespan. Yet, it has been suggested that there are phenomenological differences and differences in treatment outcomes between younger and older adults. There is, however, no consensus about the age that differentiates younger adults from older adults. As such, studies use different cut-off ages that are not well founded theoretically nor empirically. Network tree analysis was used to identify at what age adults differed in their symptom network of psychological functioning in a sample of Dutch patients diagnosed with anxiety disorders, OCD, or PTSD (N = 27,386). The networktree algorithm found a first optimal split at age 30 and a second split at age 50. Results suggest that differences in symptom networks emerge around 30 and 50 years of age, but that the core symptoms related to anxiety remain stable across age. If our results will be replicated in future studies, our study may suggest using the age split of 30 or 50 years in studies that aim to investigate differences across the lifespan. In addition, our study may suggest that age-related central symptoms are an important focus during treatment monitoring.

Topographical similarity of cortical thickness represents generalized anxiety symptoms in adolescence

Generalized anxiety disorder (GAD) is a common condition characterized by excessive and uncontrollable worry, along with its high comorbidity rates. Despite increasing efforts to identify the neural underpinnings of GAD, neuroimaging research using cortical thickness have yielded largely inconsistent results. To address this, we adopted an inter-subject representational similarity analysis framework to explore a potential nonlinear relationship between vertex-wise cortical thickness and generalized anxiety symptom severity. We utilized a sample of 120 adolescents (13-18 years of age) from the Healthy Brain Network dataset. Here, we found greater topographical resemblance among participants with heightened generalized anxiety symptoms in the left caudal anterior cingulate and pericalcarine cortex. These results were not driven by the effects of age, sex, ADHD diagnosis, and GAD diagnosis. Such associations were not observed when including a group of younger participants (11-12 years of age) for analyses, highlighting the importance of age range selection when considering the link between cortical thickness and anxiety. Our findings reveal a novel cortical thickness topography that represents generalized anxiety in adolescents, which is embedded within the shared geometries between generalized anxiety symptoms and cortical thickness.

Associations between alcohol use and sex-specific maturation of subcortical gray matter morphometry from adolescence to adulthood: Replication across two longitudinal samples

Subcortical brain morphometry matures across adolescence and young adulthood, a time when many youth engage in escalating levels of alcohol use. Initial cross-sectional studies have shown alcohol use is associated with altered subcortical morphometry. However, longitudinal evidence of sex-specific neuromaturation and associations with alcohol use remains limited. This project used generalized additive mixed models to examine sex-specific development of subcortical volumes and associations with recent alcohol use, using 7 longitudinal waves (n = 804, 51% female, ages 12-21 at baseline) from the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA). A second, independent, longitudinal dataset, with up to four waves of data (n = 467, 43% female, ages 10-18 at baseline), was used to assess replicability. Significant, replicable non-linear normative volumetric changes with age were evident in the caudate, putamen, thalamus, pallidum, amygdala and hippocampus. Significant, replicable negative associations between subcortical volume and alcohol use were found in the hippocampus in all youth, and the caudate and thalamus in female but not male youth, with significant interactions present in the caudate, thalamus and putamen. Findings suggest a structural vulnerability to alcohol use, or a predisposition to drink alcohol based on brain structure, with female youth potentially showing heightened risk, compared to male youth.

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.

Structural neurodevelopment at the individual level - a life-course investigation using ABCD, IMAGEN and UK Biobank data

Adolescents exhibit remarkable heterogeneity in the structural architecture of brain development. However, due to the lack of large-scale longitudinal neuroimaging studies, existing research has largely focused on population averages and the neurobiological basis underlying individual heterogeneity remains poorly understood. Using structural magnetic resonance imaging from the IMAGEN cohort (n=1,543), we show that adolescents can be clustered into three groups defined by distinct developmental patterns of whole-brain gray matter volume (GMV). Genetic and epigenetic determinants of group clustering and long-term impacts of neurodevelopment in mid-to-late adulthood were investigated using data from the ABCD, IMAGEN and UK Biobank cohorts. Group 1, characterized by continuously decreasing GMV, showed generally the best neurocognitive performances during adolescence. Compared to Group 1, Group 2 exhibited a slower rate of GMV decrease and worsened neurocognitive development, which was associated with epigenetic changes and greater environmental burden. Further, Group 3 showed increasing GMV and delayed neurocognitive development during adolescence due to a genetic variation, while these disadvantages were attenuated in mid-to-late adulthood. In summary, our study revealed novel clusters of adolescent structural neurodevelopment and suggested that genetically-predicted delayed neurodevelopment has limited long-term effects on mental well-being and socio-economic outcomes later in life. Our results could inform future research on policy interventions aimed at reducing the financial and emotional burden of mental illness.

Brain Structure Relations With Psychopathology Trajectories in the ABCD Study

OBJECTIVE

A general psychopathology (p) factor captures shared variation across mental disorders. Structural neural alterations have been associated with the p factor concurrently, but less is known about whether these alterations relate to within-person change in the p factor over time, especially during preadolescence, a period of neurodevelopmental changes.

METHOD

This study examined whether baseline brain structure was prospectively related to the trajectory of the p factor and specific forms of psychopathology over 2 years in 9,220 preadolescents (aged 9-10 at baseline) from the Adolescent Brain Cognitive Development Study (ABCD). Longitudinal multilevel models were conducted to determine whether baseline brain structure (volume, surface area, thickness) was associated with between-person differences and within-person change in the p factor (from a higher-order confirmatory factor model) and internalizing, externalizing, neurodevelopmental, somatization, and detachment factor scores (from a correlated factors model) over 3 study waves.

RESULTS

Smaller global volume and surface area, but not thickness, were associated with higher between-person levels of the p factor scores, which persisted over time. None of the brain structure measures were related to within-person change in the p factor scores. Lower baseline cortical thickness was associated with steeper decreases in internalizing psychopathology, which was driven by lower thickness within sensorimotor and temporal regions.

CONCLUSION

These novel results identify specific brain structure features that might contribute to transdiagnostic psychopathology development in preadolescence. Children with smaller total brain volume and surface area may be vulnerable to persistent general psychopathology during preadolescence. Cortical thinning reflective of pruning and myelination in sensorimotor and temporal brain regions specifically may protect against increases in internalizing, but not general psychopathology, during preadolescence.

Cortical Grey Matter Mediates Increases in Model-Based Control and Learning from Positive Feedback from Adolescence to Adulthood

Cognition and brain structure undergo significant maturation from adolescence into adulthood. Model-based (MB) control is known to increase across development, which is mediated by cognitive abilities. Here, we asked two questions unaddressed in previous developmental studies. First, what are the brain structural correlates of age-related increases in MB control? Second, how are age-related increases in MB control from adolescence to adulthood influenced by motivational context? A human developmental sample (n = 103; age, 12-50, male/female, 55:48) completed structural MRI and an established task to capture MB control. The task was modified with respect to outcome valence by including (1) reward and punishment blocks to manipulate the motivational context and (2) an additional choice test to assess learning from positive versus negative feedback. After replicating that an age-dependent increase in MB control is mediated by cognitive abilities, we demonstrate first-time evidence that gray matter density (GMD) in the parietal cortex mediates the increase of MB control with age. Although motivational context did not relate to age-related changes in MB control, learning from positive feedback improved with age. Meanwhile, negative feedback learning showed no age effects. We present a first report that an age-related increase in positive feedback learning was mediated by reduced GMD in the parietal, medial, and dorsolateral prefrontal cortex. Our findings indicate that brain maturation, putatively reflected in lower GMD, in distinct and partially overlapping brain regions could lead to a more efficient brain organization and might thus be a key developmental step toward age-related increases in planning and value-based choice.SIGNIFICANCE STATEMENT Changes in model-based decision-making are paralleled by extensive maturation in cognition and brain structure across development. Still, to date the neuroanatomical underpinnings of these changes remain unclear. Here, we demonstrate for the first time that parietal GMD mediates age-dependent increases in model-based control. Age-related increases in positive feedback learning were mediated by reduced GMD in the parietal, medial, and dorsolateral prefrontal cortex. A manipulation of motivational context did not have an impact on age-related changes in model-based control. These findings highlight that brain maturation in distinct and overlapping cortical regions constitutes a key developmental step toward improved value-based choices.

Linking negative affect, personality and social conditions to structural brain development during the transition from late adolescent to young adulthood

BACKGROUND

The transition from late adolescence to early adulthood is a period that experiences a surge of life changes and brain reorganization caused by internal and external factors, including negative affect, personality, and social conditions.

METHODS

Non-imaging phenotype and structural brain variables were available on 497 healthy participants (279 females and 218 males) between 17 and 22 years old. We used sparse canonical correlation analysis (sCCA) on the high-dimensional and longitudinal data to extract modes with maximum covariation between structural brain changes and negative affect, personality, and social conditions.

RESULTS

Separate sCCAs for cortical volume, cortical thickness, cortical surface area and subcortical volume confirmed that each imaging phenotype was correlated with non-imaging features (sCCA |r| range: 0.21-0.38, all p_FDR < 0.01). Bilateral superior frontal, left caudal anterior cingulate and bilateral caudate had the highest canonical cross-loadings (|ρ| = 0.15-0.32). In longitudinal data analysis, scan-interval, negative affect, and enthusiasm had the highest association with structural brain changes (|ρ| = 0.07-0.38); at baseline, intellect and politeness were associated with individual variability in the structural brain (|ρ| = 0.10-0.25).

LIMITATIONS

The present study used non-imaging variables only at baseline, making it impossible to explore the relationship between changing behavior and structural brain development.

CONCLUSIONS

Individual structural brain changes are associated with multiple factors. In addition to time-dependent variables, we find that negative affect, enthusiasm and social support play a numerically weak but significant role in structural brain development during the transition from late adolescence to young adulthood.

An open-source tool for longitudinal whole-brain and white matter lesion segmentation

In this paper we describe and validate a longitudinal method for whole-brain segmentation of longitudinal MRI scans. It builds upon an existing whole-brain segmentation method that can handle multi-contrast data and robustly analyze images with white matter lesions. This method is here extended with subject-specific latent variables that encourage temporal consistency between its segmentation results, enabling it to better track subtle morphological changes in dozens of neuroanatomical structures and white matter lesions. We validate the proposed method on multiple datasets of control subjects and patients suffering from Alzheimer's disease and multiple sclerosis, and compare its results against those obtained with its original cross-sectional formulation and two benchmark longitudinal methods. The results indicate that the method attains a higher test-retest reliability, while being more sensitive to longitudinal disease effect differences between patient groups. An implementation is publicly available as part of the open-source neuroimaging package FreeSurfer.

A framework for conceptualising early intervention for eating disorders

OBJECTIVE

This paper outlines the evidence base for early intervention for eating disorders; provides a global overview of how early intervention for eating disorders is provided in different regions and settings; and proposes policy, service, clinician and research recommendations to progress early intervention for eating disorders.

METHOD AND RESULTS

Currently, access to eating disorder treatment often takes many years or does not occur at all. This is despite neurobiological, clinical and socioeconomic evidence showing that early intervention may improve outcomes and facilitate full sustained recovery from an eating disorder. There is also considerable variation worldwide in how eating disorder care is provided, with marked inequalities in treatment provision. Despite these barriers, there are existing evidence-based approaches to early intervention for eating disorders and progress is being made in scaling these.

CONCLUSIONS

We propose action steps for the field that will transform eating disorder service provision and facilitate early detection, treatment and recovery for everyone affected by eating disorders, regardless of age, socioeconomic status and personal characteristics.

Progressive Voxel-Wise Homotopic Connectivity from childhood to adulthood: Age-related functional asymmetry in resting-state functional magnetic resonance imaging

Homotopic connectivity during resting state has been proposed as a risk marker for neurologic and psychiatric conditions, but a precise characterization of its trajectory through development is currently lacking. Voxel-Mirrored Homotopic Connectivity (VMHC) was evaluated in a sample of 85 neurotypical individuals aged 7-18 years. VMHC associations with age, handedness, sex, and motion were explored at the voxel-wise level. VMHC correlates were also explored within 14 functional networks. Primary and secondary outcomes were repeated in a sample of 107 adults aged 21-50 years. In adults, VMHC was negatively correlated with age only in the posterior insula (false discovery rate p < .05, >30-voxel clusters), while a distributed effect among the medial axis was observed in minors. Four out of 14 considered networks showed significant negative correlations between VMHC and age in minors (basal ganglia r = -.280, p = .010; anterior salience r = -.245, p = .024; language r = -.222, p = .041; primary visual r = -.257, p = .017), but not adults. In minors, a positive effect of motion on VMHC was observed only in the putamen. Sex did not significantly influence age effects on VMHC. The current study showed a specific decrease in VMHC for minors as a function of age, but not adults, supporting the notion that interhemispheric interactions can shape late neurodevelopment.

The role of brain structure in the association between pubertal timing and depression risk in an early adolescent sample (the ABCD Study®): A registered report

BACKGROUND

Earlier pubertal timing is associated with higher rates of depressive disorders in adolescence. Neuroimaging studies report brain structural associations with both pubertal timing and depression. However, whether brain structure mediates the relationship between pubertal timing and depression remains unclear.

METHODS

The current registered report examined associations between pubertal timing (indexed via perceived pubertal development), brain structure (cortical and subcortical metrics, and white matter microstructure) and depressive symptoms in a large sample (N = ∼5000) of adolescents (aged 9-13 years) from the Adolescent Brain Cognitive Development (ABCD) Study. We used three waves of follow-up data when the youth were aged 10-11 years, 11-12 years, and 12-13 years, respectively. We used generalised linear-mixed models (H1) and structural equation modelling (H2 & H3) to test our hypotheses.

HYPOTHESES

We hypothesised that earlier pubertal timing at Year 1 would be associated with increased depressive symptoms at Year 3 (H1), and that this relationship would be mediated by global (H2a-b) and regional (H3a-g) brain structural measures at Year 2. Global measures included reduced cortical volume, thickness, surface area and sulcal depth. Regional measures included reduced cortical thickness and volume in temporal and fronto-parietal areas, increased cortical volume in the ventral diencephalon, increased sulcal depth in the pars orbitalis, and reduced fractional anisotropy in the cortico-striatal tract and corpus callosum. These regions of interest were informed by our pilot analyses using baseline ABCD data when the youth were aged 9-10 years.

RESULTS

Earlier pubertal timing was associated with increased depressive symptoms two years later. The magnitude of effect was stronger in female youth and the association remained significant when controlling for parental depression, family income, and BMI in females but not in male youth. Our hypothesised brain structural measures did not however mediate the association between earlier pubertal timing and later depressive symptoms.

CONCLUSION

The present results demonstrate that youth, particularly females, who begin puberty ahead of their peers are at an increased risk for adolescent-onset depression. Future work should explore additional biological and socio-environmental factors that may affect this association so that we can identify targets for intervention to help these at-risk youth.