The purpose of the present study was to detail the childhood developmental course of different white matter (WM) characteristics. In a longitudinal diffusion tensor imaging (DTI) study of 159 healthy children between 4 and 11years scanned twice, we used tract-based spatial statistics as well as delineation of 15 major WM tracts to characterize the regional pattern of change in fractional anisotropy (FA), mean (MD), radial (RD) and axial diffusivity (AD). We tested whether there were decelerations of change with increasing age globally and tract-wise, and also illustrated change along medial-to-lateral, posterior-to-anterior and inferior-to-superior gradients. We found a significant linear increase in global FA, and decrease in MD and RD over time. For mean AD, a weak decrease was observed. The developmental changes in specific WM tracts showed regional differences. Eight WM tracts showed non-linear development patterns for one or several DTI metrics, with a deceleration in change with age. Sex did not affect change in any DTI metric. Overall, greater rate of change was found in the left hemisphere. Spatially, there was a posterior-to-anterior gradient of change with greater change in frontal regions for all metrics. The current study provides a comprehensive characterization of the regional patters of change in WM microstructure across pre-adolescence childhood.

The onset of adolescence in humans is marked by hormonal changes that give rise to secondary sexual characteristics, noted as puberty. It has, however, proven challenging to unravel to what extent pubertal changes may have organizing effects on the brain beyond chronological age, as reported in animal studies. The present longitudinal study aimed to characterize the unique effects of age and puberty on subcortical brain volumes and included three waves of data collection at two-year intervals and 680 T1-weighted MRI scans of 271 participants (54% females) aged between 8 and 29 years old. Generalized additive mixed model procedures were used to assess the effects of age, self-report pubertal status and testosterone level on basal ganglia, thalamus, hippocampus, amygdala and cerebellum gray matter volumes. We observed age-related increases in putamen and pallidum volumes, and decreases in accumbens and thalamus volumes, all show larger volumes in boys than girls. Only the cerebellum showed an interaction effect of age by sex, such that males showed prolonged increases in cerebellar volume than females. Next, we showed that changes in self-report puberty status better described developmental change than chronological age for most structures in males, and for caudate, pallidum and hippocampal volumes in females. Furthermore, changes in testosterone level were related to development of pallidum, accumbens, hippocampus and amygdala volumes in males and caudate and hippocampal volumes in females. The modeling approach of the present study allowed us to characterize the complex interactions between chronological age and pubertal maturational changes, and the findings indicate puberty unique changes in brain structure that are sex specific.

The developmental patterns of subcortical brain volumes in males and females observed in previous studies have been inconsistent. To help resolve these discrepancies, we examined developmental trajectories using three independent longitudinal samples of participants in the age-span of 8-22 years (total 216 participants and 467 scans). These datasets, including Pittsburgh (PIT; University of Pittsburgh, USA), NeuroCognitive Development (NCD; University of Oslo, Norway), and Orygen Adolescent Development Study (OADS; The University of Melbourne, Australia), span three countries and were analyzed together and in parallel using mixed-effects modeling with both generalized additive models and general linear models. For all regions and across all samples, males were found to have significantly larger volumes as compared to females, and significant sex differences were seen in age trajectories over time. However, direct comparison of sample trajectories and sex differences identified within samples were not consistent. The trajectories for the amygdala, putamen, and nucleus accumbens were most consistent between the three samples. Our results suggest that even after using similar preprocessing and analytic techniques, additional factors, such as image acquisition or sample composition may contribute to some of the discrepancies in sex specific patterns in subcortical brain changes across adolescence, and highlight region-specific variations in congruency of developmental trajectories.

Continued advances in neuroimaging technologies and statistical modelling capabilities have improved our knowledge of structural brain development in children and adolescents. While this has provided an increasingly nuanced understanding of brain development, the field is still plagued by inconsistent findings. This review highlights the methodological diversity in existing longitudinal magnetic resonance imaging (MRI) studies on structural brain development during childhood and adolescence, and addresses how such variation might contribute to inconsistencies in the literature. We discuss the impact of method choices at multiple decision points across the research process, from study design and sample selection, to image processing and statistical analysis. We also highlight the extent to which different methodological considerations have been empirically examined, drawing attention to specific areas that would benefit from future investigation. Where appropriate, we recommend certain best practices that would be beneficial for the field to adopt, including greater completeness and transparency in reporting methods, in order to ultimately develop an accurate and detailed understanding of normative child and adolescent brain development.

Cerebral myeloarchitecture shows substantial development across childhood and adolescence, and aberrations in these trajectories are relevant for a range of mental disorders. Differential myelination between intracortical and subjacent white matter can be approximated using signal intensities in T1-weighted magnetic resonance imaging.

Low-frequency 1q21.1 distal deletion and duplication copy number variant (CNV) carriers are predisposed to multiple neurodevelopmental disorders, including schizophrenia, autism and intellectual disability. Human carriers display a high prevalence of micro- and macrocephaly in deletion and duplication carriers, respectively. The underlying brain structural diversity remains largely unknown. We systematically called CNVs in 38 cohorts from the large-scale ENIGMA-CNV collaboration and the UK Biobank and identified 28 1q21.1 distal deletion and 22 duplication carriers and 37,088 non-carriers (48% male) derived from 15 distinct magnetic resonance imaging scanner sites. With standardized methods, we compared subcortical and cortical brain measures (all) and cognitive performance (UK Biobank only) between carrier groups also testing for mediation of brain structure on cognition. We identified positive dosage effects of copy number on intracranial volume (ICV) and total cortical surface area, with the largest effects in frontal and cingulate cortices, and negative dosage effects on caudate and hippocampal volumes. The carriers displayed distinct cognitive deficit profiles in cognitive tasks from the UK Biobank with intermediate decreases in duplication carriers and somewhat larger in deletion carriers-the latter potentially mediated by ICV or cortical surface area. These results shed light on pathobiological mechanisms of neurodevelopmental disorders, by demonstrating gene dose effect on specific brain structures and effect on cognitive function.

Many workflows and tools that aim to increase the reproducibility and replicability of research findings have been suggested. In this review, we discuss the opportunities that these efforts offer for the field of developmental cognitive neuroscience, in particular developmental neuroimaging. We focus on issues broadly related to statistical power and to flexibility and transparency in data analyses. Critical considerations relating to statistical power include challenges in recruitment and testing of young populations, how to increase the value of studies with small samples, and the opportunities and challenges related to working with large-scale datasets. Developmental studies involve challenges such as choices about age groupings, lifespan modelling, analyses of longitudinal changes, and data that can be processed and analyzed in a multitude of ways. Flexibility in data acquisition, analyses and description may thereby greatly impact results. We discuss methods for improving transparency in developmental neuroimaging, and how preregistration can improve methodological rigor. While outlining challenges and issues that may arise before, during, and after data collection, solutions and resources are highlighted aiding to overcome some of these. Since the number of useful tools and techniques is ever-growing, we highlight the fact that many practices can be implemented stepwise.

Human brain development involves spatially and temporally heterogeneous changes, detectable across a wide range of magnetic resonance imaging (MRI) measures. Investigating the interplay between multimodal MRI and polygenic scores (PGS) for personality traits associated with mental disorders in youth may provide new knowledge about typical and atypical neurodevelopment. We derived independent components across cortical thickness, cortical surface area, and grey/white matter contrast (GWC) (n = 2596, 3-23 years), and tested for associations between these components and age, sex and-, in a subsample (n = 878), PGS for neuroticism. Age was negatively associated with a single-modality component reflecting higher global GWC, and additionally with components capturing common variance between global thickness and GWC, and several multimodal regional patterns. Sex differences were found for components primarily capturing global and regional surface area (boys > girls), but also regional cortical thickness. For PGS for neuroticism, we found weak and bidirectional associations with a component reflecting right prefrontal surface area. These results indicate that multimodal fusion is sensitive to age and sex differences in brain structure in youth, but only weakly to polygenic load for neuroticism.

Two distinctly different maturational processes - cortical thinning and white matter maturation - take place in the brain as we mature from late childhood to adulthood. To what extent does each contribute to the development of complex cognitive functions like working memory? The independent and joint contributions of cortical thickness of regions of the left fronto-parietal network and the diffusion characteristics of the connecting pathway of the left superior longitudinal fasciculus (SLF) in accounting for verbal working memory performance were investigated, using a predefined regions of interest-approach. 108 healthy participants aged 8-19 years underwent MRI, including anatomical and diffusion tensor imaging (DTI), as well as cognitive testing using a digit span task. Radial diffusivity of the SLF, as well as cortical thickness of supramarginal gyrus and rostral middle frontal cortex, were negatively related to digit span forwards performance, independently of age. Radial diffusivity of the SLF was also negatively related to digit span backwards. A multi-modal analysis showed that cortical thickness and SLF microstructure were complementary in explaining working memory span. Furthermore, SLF microstructure and cortical thickness had different impact on working memory performance during the developmental period, suggesting a complex developmental interplay. The results indicate that cortical and white matter maturation each play unique roles in the development of working memory.

Early-life development is characterized by dramatic changes, impacting lifespan function more than changes in any other period. Developmental origins of neurocognitive late-life functions are acknowledged, but detailed longitudinal magnetic resonance imaging studies of brain maturation and direct comparisons with aging are lacking. To these aims, a novel method was used to measure longitudinal volume changes in development (n=85, 8-22 years) and aging (n=142, 60-91 years). Developmental reductions exceeded 1% annually in much of the cortex, more than double to that seen in aging, with a posterior-to-anterior gradient. Cortical reductions were greater than the subcortical during development, while the opposite held in aging. The pattern of lateral cortical changes was similar across development and aging, but the pronounced medial temporal reduction in aging was not precast in development. Converging patterns of change in adolescents and elderly, particularly in the medial prefrontal areas, suggest that late developed cortices are especially vulnerable to atrophy in aging. A key question in future research will be to disentangle the neurobiological underpinnings for the differences and the similarities between brain changes in development and aging.

Detailed descriptions of the development of the hippocampus promise to shed light on the neural foundation of development of memory and other cognitive functions, as well as the emergence of major mental disorders. Hippocampus is a heterogeneous structure with a well characterized internal complexity, but development of its distinct subregions in humans has remained poorly described. We analyzed magnetic resonance imaging (MRI) data from a large longitudinal sample (270 participants, 678 scans) using an automated segmentation tool and mixed models to delineate the development of hippocampal subregion volumes from childhood to adulthood. We also examined sex differences in subregion volumes and their development, and associations between hippocampal subregions and general cognitive ability. Nonlinear developmental trajectories with early volume increases were observed for subiculum, cornu ammonis (CA) 1, molecular layer (ML) and fimbria. In contrast, parasubiculum, presubiculum, CA2/3, CA4 and the granule cell layer of the dentate gyrus (GC-DG) showed linear volume decreases. No sex differences were found in hippocampal subregion development. Finally, general cognitive ability was positively associated with CA2/3 and CA4 volumes, as well as with ML development. In conclusion, hippocampal subregions appear to develop in diversified ways across adolescence, and specific subregions may link to general cognitive level.

Delineating the association of age and cortical thickness in healthy individuals is critical given the association of cortical thickness with cognition and behavior. Previous research has shown that robust estimates of the association between age and brain morphometry require large-scale studies. In response, we used cross-sectional data from 17,075 individuals aged 3-90 years from the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to infer age-related changes in cortical thickness. We used fractional polynomial (FP) regression to quantify the association between age and cortical thickness, and we computed normalized growth centiles using the parametric Lambda, Mu, and Sigma method. Interindividual variability was estimated using meta-analysis and one-way analysis of variance. For most regions, their highest cortical thickness value was observed in childhood. Age and cortical thickness showed a negative association; the slope was steeper up to the third decade of life and more gradual thereafter; notable exceptions to this general pattern were entorhinal, temporopolar, and anterior cingulate cortices. Interindividual variability was largest in temporal and frontal regions across the lifespan. Age and its FP combinations explained up to 59% variance in cortical thickness. These results may form the basis of further investigation on normative deviation in cortical thickness and its significance for behavioral and cognitive outcomes.

Age has a major effect on brain volume. However, the normative studies available are constrained by small sample sizes, restricted age coverage and significant methodological variability. These limitations introduce inconsistencies and may obscure or distort the lifespan trajectories of brain morphometry. In response, we capitalized on the resources of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to examine age-related trajectories inferred from cross-sectional measures of the ventricles, the basal ganglia (caudate, putamen, pallidum, and nucleus accumbens), the thalamus, hippocampus and amygdala using magnetic resonance imaging data obtained from 18,605 individuals aged 3-90 years. All subcortical structure volumes were at their maximum value early in life. The volume of the basal ganglia showed a monotonic negative association with age thereafter; there was no significant association between age and the volumes of the thalamus, amygdala and the hippocampus (with some degree of decline in thalamus) until the sixth decade of life after which they also showed a steep negative association with age. The lateral ventricles showed continuous enlargement throughout the lifespan. Age was positively associated with inter-individual variability in the hippocampus and amygdala and the lateral ventricles. These results were robust to potential confounders and could be used to examine the functional significance of deviations from typical age-related morphometric patterns.

Intellectual abilities are supported by a large-scale fronto-parietal brain network distributed across both cerebral hemispheres. This bihemispheric network suggests a functional relevance of inter-hemispheric coordination, a notion which is supported by a series of recent structural magnetic resonance imaging (MRI) studies demonstrating correlations between intelligence scores (IQ) and corpus-callosum anatomy. However, these studies also reveal an age-related dissociation: mostly positive associations are reported in adult samples, while negative associations are found in developing samples. In the present study, we re-examine the association between corpus callosum and intelligence measures in a large (734 datasets from 495 participants) developmental mixed cross-sectional and longitudinal sample (6.4-21.9 years) using raw test scores rather than deviation IQ measures to account for the ongoing cognitive development in this age period. Analyzing mid-sagittal measures of regional callosal thickness, a positive association in the splenium of the corpus callosum was found for both verbal and performance raw test scores. This association was not present when the participants' age was considered in the analysis. Thus, we did not reveal any association that cannot be explained by a temporal co-occurrence of overall developmental trends in intellectual abilities and corpus callosum maturation in the present developing sample.

Research has demonstrated associations between pubertal development and brain maturation. However, existing studies have been limited by small samples, cross-sectional designs, and inconclusive findings regarding directionality of effects and sex differences. We examined the longitudinal temporal coupling of puberty status assessed using the Pubertal Development Scale (PDS) and magnetic resonance imaging (MRI)-based grey and white matter brain structure. Our sample consisted of 8896 children and adolescents at baseline (mean age = 9.9) and 6099 at follow-up (mean age = 11.9) from the Adolescent Brain and Cognitive Development (ABCD) Study cohort. Applying multigroup Bivariate Latent Change Score (BLCS) models, we found that baseline PDS predicted the rate of change in cortical thickness among females and rate of change in cortical surface area for both males and females. We also found a correlation between baseline PDS and surface area and co-occurring changes over time in males. Diffusion tensor imaging (DTI) analyses revealed correlated change between PDS and fractional anisotropy (FA) for both males and females, but no significant associations for mean diffusivity (MD). Our results suggest that pubertal status predicts cortical maturation, and that the strength of the associations differ between sex. Further research spanning the entire duration of puberty is needed to understand the extent and contribution of pubertal development on the youth brain.

The lack of robust neuroanatomical markers of psychosis risk has been traditionally attributed to heterogeneity. A complementary hypothesis is that variation in neuroanatomical measures in the majority of individuals at psychosis risk may be nested within the range observed in healthy individuals.

Abnormalities in brain structure are shared across diagnostic categories. Given the high rate of comorbidity, the interplay of relevant behavioural factors may also cross these classic boundaries.

Basic perspective taking and mentalizing abilities develop in childhood, but recent studies indicate that the use of social perspective taking to guide decisions and actions has a prolonged development that continues throughout adolescence. Here, we aimed to replicate this research and investigate the hypotheses that individual differences in social perspective taking in adolescence are associated with real-life prosocial and antisocial behavior and differences in brain structure. We used an experimental approach and a large cross-sectional sample (n = 293) of participants aged 7-26 years old to assess age-related improvement in social perspective taking usage during performance of a version of the director task. In subsamples, we then tested how individual differences in social perspective taking were related to self-reported prosocial behavior and peer relationship problems on the Strengths and Difficulties Questionnaire (n = 184) and to MRI measures of regional cortical thickness and surface area (n = 226). The pattern of results in the director task replicated previous findings by demonstrating continued improvement in use of social perspective taking across adolescence. The study also showed that better social perspective taking usage is associated with more self-reported prosocial behavior, as well as to thinner cerebral cortex in regions in the left hemisphere encompassing parts of the caudal middle frontal and precentral gyri and lateral parietal regions. These associations were observed independently of age and might partly reflect individual developmental variability. The relevance of cortical development was additionally supported by indirect effects of age on social perspective taking usage via cortical thickness. (PsycINFO Database Record

Brain structural alterations and cognitive dysfunction are independent predictors for poor clinical outcome in schizophrenia, and the associations between these domains remains unclear. We employed a novel, multiblock partial least squares correlation (MB-PLS-C) technique and investigated multivariate cortico-cognitive patterns in patients with treatment-resistant schizophrenia (TRS) and matched healthy controls (HC).

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.