Highlights • Physical and hormonal markers of puberty have been linked with brain structure. • Challenges are discussed, including capturing variability in hormone levels. • More research is needed ...on individual differences in pubertal onset and progression.
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.
In May 2017, a two-day workshop was held in Los Angeles (California, U.S.A.) to gather practitioners who work with low-cost sensors used to make air quality measurements. The community of practice ...included individuals from academia, industry, non-profit groups, community-based organizations, and regulatory agencies. The group gathered to share knowledge developed from a variety of pilot projects in hopes of advancing the collective knowledge about how best to use low-cost air quality sensors. Panel discussion topics included: (1) best practices for deployment and calibration of low-cost sensor systems, (2) data standardization efforts and database design, (3) advances in sensor calibration, data management, and data analysis and visualization, and (4) lessons learned from research/community partnerships to encourage purposeful use of sensors and create change/action. Panel discussions summarized knowledge advances and project successes while also highlighting the questions, unresolved issues, and technological limitations that still remain within the low-cost air quality sensor arena.
A fundamental task in neuroscience is to characterize the brain's developmental course. While replicable group-level models of structural brain development from childhood to adulthood have recently ...been identified, we have yet to quantify and understand individual differences in structural brain development. The present study examined inter-individual variability and sex differences in changes in brain structure, as assessed by anatomical MRI, across ages 8.0–26.0 years in 269 participants (149 females) with three time points of data (807 scans), drawn from three longitudinal datasets collected in the Netherlands, Norway, and USA. We further investigated the relationship between overall brain size and developmental changes, as well as how females and males differed in change variability across development. There was considerable inter-individual variability in the magnitude of changes observed for all examined brain measures. The majority of individuals demonstrated decreases in total gray matter volume, cortex volume, mean cortical thickness, and white matter surface area in mid-adolescence, with more variability present during the transition into adolescence and the transition into early adulthood. While most individuals demonstrated increases in white matter volume in early adolescence, this shifted to a majority demonstrating stability starting in mid-to-late adolescence. We observed sex differences in these patterns, and also an association between the size of an individual's brain structure and the overall rate of change for the structure. The present study provides new insight as to the amount of individual variance in changes in structural morphometrics from late childhood to early adulthood in order to obtain a more nuanced picture of brain development. The observed individual- and sex-differences in brain changes also highlight the importance of further studying individual variation in developmental patterns in healthy, at-risk, and clinical populations.
Sex hormones have been shown to contribute to the organization and function of the brain during puberty and adolescence. Moreover, it has been suggested that distinct hormone changes in girls versus ...boys may contribute to the emergence of sex differences in internalizing and externalizing behavior during adolescence. In the current longitudinal study, the influence of within-subject changes in puberty (physical and hormonal) on cortical thickness and surface area was examined across a 2-year span, while controlling for age. Greater increases in Tanner Stage predicted less superior frontal thinning and decreases in precuneus surface area in both sexes. Significant Tanner Stage and sex interactions were also seen, with less right superior temporal thinning in girls but not boys, as well as greater decreases in the right bank of the superior temporal sulcus surface area in boys compared to girls. In addition, within-subject changes in testosterone over the 2-year follow-up period were found to relate to decreases in middle superior frontal surface area in boys, but increases in surface area in girls. Lastly, larger increases in estradiol in girls predicted greater middle temporal lobe thinning. These results show that within-subject physical and hormonal markers of puberty relate to region and sex-specific changes in cortical development across adolescence.
During adolescence, numerous factors influence the organization of the brain. It is unclear what influence sex and puberty have on white matter microstructure, as well as the role that rapidly ...increasing sex steroids play.
White matter microstructure was examined in 77 adolescents (ages 10-16) using diffusion tensor imaging. Multiple regression analyses were performed to examine the relationships between fractional anisotropy (FA) and mean diffusivity (MD) and sex, puberty, and their interaction, controlling for age. Follow-up analyses determined if sex steroids predicted microstructural characteristics in sexually dimorphic and pubertal-related white matter regions, as well as in whole brain.
Boys had higher FA in white matter carrying corticospinal, long-range association, and cortico-subcortical fibers, and lower MD in frontal and temporal white matter compared with girls. Pubertal development was related to higher FA in the insula, while a significant sex-by-puberty interaction was seen in superior frontal white matter. In boys, testosterone predicted white matter integrity in sexually dimorphic regions as well as whole brain FA, whereas estradiol showed a negative relationship with FA in girls.
Sex differences and puberty uniquely relate to white matter microstructure in adolescents, which can partially be explained by sex steroids.
•Largest study to date on fine particulate matter (PM2.5) and brain in children.•Individual residential PM2.5 exposure assigned for 10,343 U.S. children at 21 sites.•PM2.5 associated with regional- ...and hemisphere-specific brain differences.•PM2.5 was not associated with NIH Toolbox performance.•Findings were similar in both boys and girls.
Emerging findings have increased concern that exposure to fine particulate matter air pollution (aerodynamic diameter ≤ 2.5 μm; PM2.5) may be neurotoxic, even at lower levels of exposure. Yet, additional studies are needed to determine if exposure to current PM2.5 levels may be linked to hemispheric and regional patterns of brain development in children across the United States.
We examined the cross-sectional associations between geocoded measures of concurrent annual average outdoor PM2.5 exposure, regional- and hemisphere-specific differences in brain morphometry and cognition in 10,343 9- and 10- year-old children.
High-resolution structural T1-weighted brain magnetic resonance imaging (MRI) and NIH Toolbox measures of cognition were collected from children at ages 9–10 years. FreeSurfer was used to quantify cortical surface area, cortical thickness, as well as subcortical and cerebellum volumes in each hemisphere. PM2.5 concentrations were estimated using an ensemble-based model approach and assigned to each child’s primary residential address collected at the study visit. We used mixed-effects models to examine regional- and hemispheric- effects of PM2.5 exposure on brain estimates and cognition after considering nesting of participants by familial relationships and study site, adjustment for socio-demographic factors and multiple comparisons.
Annual residential PM2.5 exposure (7.63 ± 1.57 µg/m3) was associated with hemispheric specific differences in gray matter across cortical regions of the frontal, parietal, temporal and occipital lobes as well as subcortical and cerebellum brain regions. There were hemispheric-specific associations between PM2.5 exposures and cortical surface area in 9/31 regions; cortical thickness in 22/27 regions; and volumes of the thalamus, pallidum, and nucleus accumbens. We found neither significant associations between PM2.5 and task performance on individual measures of neurocognition nor evidence that sex moderated the observed associations.
Even at relatively low-levels, current PM2.5 exposure across the U.S. may be an important environmental factor influencing patterns of structural brain development in childhood. Prospective follow-up of this cohort will help determine how current levels of PM2.5 exposure may affect brain development and subsequent risk for cognitive and emotional problems across adolescence.
► Adolescent working memory improves as a function of age and pubertal status. ► Adolescents show lateralized brain activity during spatial and verbal working memory. ► Adolescents show age-related ...changes in brain activation during working memory. ► Adolescents do not show developmental change in brain activity lateralization.
Adult functional magnetic resonance imaging (fMRI) literature suggests that a left–right hemispheric dissociation may exist between verbal and spatial working memory (WM), respectively. However, investigation of this type has been obscured by incomparable verbal and spatial WM tasks and/or visual inspection at arbitrary thresholds as means to assess lateralization. Furthermore, it is unclear whether this hemispheric lateralization is present during adolescence, a time in which WM skills are improving, and whether there is a developmental association with laterality of brain functioning. This study used comparable verbal and spatial WM n-back tasks during fMRI and a bootstrap analysis approach to calculate lateralization indices (LIs) across several thresholds to examine the potential of a left–right WM hemispheric dissociation in healthy adolescents. We found significant left hemispheric lateralization for verbal WM, most notably in the frontal and parietal lobes, as well as right hemisphere lateralization for spatial WM, seen in frontal and temporal cortices. Although no significant relationships were observed between LI and age or LI and performance, significant age-related patterns of brain activity were demonstrated during both verbal and spatial WM. Specifically, increased adolescent age was associated with less activity in the default mode brain network during verbal WM. In contrast, increased adolescent age was associated with greater activity in task-positive posterior parietal cortex during spatial working memory. Our findings highlight the importance of utilizing non-biased statistical methods and comparable tasks for determining patterns of functional lateralization. Our findings also suggest that, while a left–right hemispheric dissociation of verbal and spatial WM is apparent by early adolescence, age-related changes in functional activation during WM are also present.
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