Over the past two decades, there has been a tremendous increase in our understanding of structural and functional brain development in adolescence. However, understanding the role of puberty in this ...process has received much less attention. This review examines this relationship by summarizing recent research studies where the role of puberty was investigated in relation to brain structure, connectivity, and task‐related functional magnetic resonance imaging (fMRI). The studies together suggest that puberty may contribute to adolescent neural reorganization and maturational advancement, and sex differences also emerge in puberty. The current body of work shows some mixed results regarding impact and exact direction of pubertal influence. We discuss several limitations of current studies and propose future directions on how to move the field forward.
Before we can assess and interpret how developmental changes in human brain structure relate to cognition, affect, and motivation, and how these processes are perturbed in clinical or at-risk ...populations, we must first precisely understand typical brain development and how changes in different structural components relate to each other. We conducted a multisample magnetic resonance imaging study to investigate the development of cortical volume, surface area, and thickness, as well as their inter-relationships, from late childhood to early adulthood (7-29 years) using four separate longitudinal samples including 388 participants and 854 total scans. These independent datasets were processed and quality-controlled using the same methods, but analyzed separately to study the replicability of the results across sample and image-acquisition characteristics. The results consistently showed widespread and regionally variable nonlinear decreases in cortical volume and thickness and comparably smaller steady decreases in surface area. Further, the dominant contributor to cortical volume reductions during adolescence was thinning. Finally, complex regional and topological patterns of associations between changes in surface area and thickness were observed. Positive relationships were seen in sulcal regions in prefrontal and temporal cortices, while negative relationships were seen mainly in gyral regions in more posterior cortices. Collectively, these results help resolve previous inconsistencies regarding the structural development of the cerebral cortex from childhood to adulthood, and provide novel insight into how changes in the different dimensions of the cortex in this period of life are inter-related.
Different measures of brain anatomy develop differently across adolescence. Their precise trajectories and how they relate to each other throughout development are important to know if we are to fully understand both typical development and disorders involving aberrant brain development. However, our understanding of such trajectories and relationships is still incomplete. To provide accurate characterizations of how different measures of cortical structure develop, we performed an MRI investigation across four independent datasets. The most profound anatomical change in the cortex during adolescence was thinning, with the largest decreases observed in the parietal lobe. There were complex regional patterns of associations between changes in surface area and thickness, with positive relationships seen in sulcal regions in prefrontal and temporal cortices, and negative relationships seen mainly in gyral regions in more posterior cortices.
Longitudinal studies including brain measures acquired through magnetic resonance imaging (MRI) have enabled population models of human brain development, crucial for our understanding of typical ...development as well as neurodevelopmental disorders. Brain development in the first two decades generally involves early cortical grey matter volume (CGMV) increases followed by decreases, and monotonic increases in cerebral white matter volume (CWMV). However, inconsistencies regarding the precise developmental trajectories call into question the comparability of samples. This issue can be addressed by conducting a comprehensive study across multiple datasets from diverse populations. Here, we present replicable models for gross structural brain development between childhood and adulthood (ages 8–30years) by repeating analyses in four separate longitudinal samples (391 participants; 852 scans). In addition, we address how accounting for global measures of cranial/brain size affect these developmental trajectories. First, we found evidence for continued development of both intracranial volume (ICV) and whole brain volume (WBV) through adolescence, albeit following distinct trajectories. Second, our results indicate that CGMV is at its highest in childhood, decreasing steadily through the second decade with deceleration in the third decade, while CWMV increases until mid-to-late adolescence before decelerating. Importantly, we show that accounting for cranial/brain size affects models of regional brain development, particularly with respect to sex differences. Our results increase confidence in our knowledge of the pattern of brain changes during adolescence, reduce concerns about discrepancies across samples, and suggest some best practices for statistical control of cranial volume and brain size in future studies.
Puberty is characterized by hormonal, physical and psychological transformation. The human brain undergoes significant changes between childhood and adulthood, but little is known about how puberty ...influences its structural development. Using a longitudinal sample of 711 magnetic resonance imaging scans from 275 individuals aged 7–20years, we examined how subcortical brain regions change in relation to puberty. Our regions of interest included the amygdala, hippocampus and corpus striatum including the nucleus accumbens (NA), caudate, putamen and globus pallidus (GP). Pubertal development was significantly related to structural volume in all six regions in both sexes. Pubertal development and age had both independent and interactive influences on volume for the amygdala, hippocampus and putamen in both sexes, and the caudate in females. There was an interactive puberty-by-age effect on volume for the NA and GP in both sexes, and the caudate in males. These findings suggest a significant role for puberty in structural brain development.
•Subcortical regions continue to develop through puberty in females and males.•The developmental trajectories vary between subcortical regions.•Puberty and age have independent and interactive influences on this development.
Correspondence to Dr Anne-Lise Goddings, University College London Great Ormond Street Institute of Child Health, London WC1N 1EH, UK; anne-lise.goddings@ucl.ac.uk There is growing scrutiny regarding ...the quality of inpatient care for adolescents in England, and whether services can meet their unique medical and psychosocial needs.1 Adolescents represent a substantial proportion of paediatric health service users and have a rising chronic disease burden. UpSet plot showing the number and frequency of individual and combination of different staff groups (consultant with a special interest in adolescent medicine, nurse with a special interest in adolescent medicine, youth worker (YW), psychologist, and Child and Adolescent Mental Health Services (CAMHS) liaison nurse) employed by paediatric departments. National survey of use of hospital beds by adolescents aged 12 to 19 in the United Kingdom.
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.
•Sex differences were seen in age trajectories over time based on three samples.•General additive models can assess presumed sex differences in trajectory shape.•Despite identical data processing and analysis, discrepancies existed between the samples.•Amygdala, putamen, and nucleus accumbens patterns were most consistent between samples.
Regions of the human brain develop at different rates across the first two decades of life, with some maturing before others. It has been hypothesized that a mismatch in the timing of maturation ...between subcortical regions (involved in affect and reward processing) and prefrontal regions (involved in cognitive control) underlies the increase in risk-taking and sensation-seeking behaviors observed during adolescence. Most support for this ‘dual systems' hypothesis relies on cross-sectional data, and it is not known whether this pattern is present at an individual level. The current study utilizes longitudinal structural magnetic resonance imaging (MRI) data to describe the developmental trajectories of regions associated with risk-taking and sensation-seeking behaviors, namely, the amygdala, nucleus accumbens (NAcc) and prefrontal cortex (PFC). Structural trajectories of gray matter volumes were analyzed using FreeSurfer in 33 participants aged 7-30 years, each of whom had at least three high-quality MRI scans spanning three developmental periods: late childhood, adolescence and early adulthood (total 152 scans). The majority of individuals in our sample showed relatively earlier maturation in the amygdala and/or NAcc compared to the PFC, providing evidence for a mismatch in the timing of structural maturation between these structures. We then related individual developmental trajectories to retrospectively assessed self-reported risk-taking and sensation-seeking behaviors during adolescence in a subsample of 24 participants. Analysis of this smaller sample failed to find a relationship between the presence of a mismatch in brain maturation and risk-taking and sensation-seeking behaviors during adolescence. Taken together, it appears that the developmental mismatch in structural brain maturation is present in neurotypically developing individuals. This pattern of development did not directly relate to self-reported behaviors at an individual level in our sample, highlighting the need for prospective studies combining anatomical and behavioral measures.
Diffusion magnetic resonance imaging (dMRI) continues to grow in popularity as a useful neuroimaging method to study brain development, and longitudinal studies that track the same individuals over ...time are emerging. Over the last decade, seminal work using dMRI has provided new insights into the development of brain white matter (WM) microstructure, connections and networks throughout childhood and adolescence. This review provides an introduction to dMRI, both diffusion tensor imaging (DTI) and other dMRI models, as well as common acquisition and analysis approaches. We highlight the difficulties associated with ascribing these imaging measurements and their changes over time to specific underlying cellular and molecular events. We also discuss selected methodological challenges that are of particular relevance for studies of development, including critical choices related to image acquisition, image analysis, quality control assessment, and the within-subject and longitudinal reliability of dMRI measurements. Next, we review the exciting progress in the characterization and understanding of brain development that has resulted from dMRI studies in childhood and adolescence, including brief overviews and discussions of studies focusing on sex and individual differences. Finally, we outline future directions that will be beneficial to the field.
Adolescence is marked by the onset of puberty, which is associated with an increase in mental health difficulties, particularly in girls. Social and self‐referential processes also develop during ...this period: adolescents become more aware of others’ perspectives, and judgements about themselves become less favourable. In the current study, data from 119 girls (from London, UK) aged 9–16 years were collected at two‐time points (between 2019 and 2021) to investigate the relationship between puberty and difficulties in mental health and emotion regulation, as well as the role of self‐referential and social processing in this relationship. Structural equation modelling showed that advanced pubertal status predicted greater mental health and emotion regulation difficulties, including depression and anxiety, rumination and overall difficulties in emotion regulation, and in mental health and behaviour. Advanced pubertal status also predicted greater perspective‐taking abilities and negative self‐schemas. Exploratory analyses showed that negative self‐schemas mediated the relationships between puberty and rumination, overall emotion regulation difficulties, and depression (although these effects were small and would not survive correction for multiple comparisons). The results suggest that advanced pubertal status is associated with higher mental health and emotion regulation problems during adolescence and that negative self‐schemas may play a role in this association.
Research Highlights
This study investigates the relationship between puberty, mental health, emotion regulation difficulties, and social and self‐referential processing in girls aged 9–16 years.
Advanced pubertal status was associated with worse mental health and greater emotion regulation difficulties, better perspective‐taking abilities and negative self‐schemas.
Negative self‐schemas may play a role in the relationships between advanced pubertal status and depression, and advanced pubertal status and emotion regulation difficulties, including rumination.
•We review links between white matter development and executive functions.•Better inhibition is associated with higher fractional anisotropy in frontal regions.•Working memory is associated with ...higher fractional anisotropy in several areas.•There are few studies in this area and more research is needed.
Diffusion magnetic resonance imaging (dMRI) provides indirect measures of white matter microstructure that can be used to make inferences about structural connectivity within the brain. Over the last decade, a growing literature of cross-sectional and longitudinal studies have documented relationships between dMRI indices and cognitive development. In this review, we provide a brief overview of dMRI methods and how they can be used to study white matter and connectivity and review the extant literature examining the links between dMRI indices and executive functions during development. We explore the links between white matter microstructure and specific executive functions: inhibition, working memory and cognitive shifting, as well as performance on complex executive function tasks. Concordance in findings across studies are highlighted, and potential explanations for discrepancies between results, together with challenges with using dMRI in child and adolescent populations, are discussed. Finally, we explore future directions that are necessary to better understand the links between child and adolescent development of structural connectivity of the brain and executive functions.
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