How does the human brain structurally change as we grow up?

What was the primary objective of this collaborative study regarding structural brain developmental trajectories?

The study aimed to replicate gross brain developmental trajectories across four independent longitudinal samples and investigate how accounting for global measures of brain size (ICV or WBV) affects these trajectories.

Source: Structural brain development between childhood and adulthood: Convergence across four longitudinal samples · DOI · quote verified

From which countries and institutions were the four longitudinal datasets in this study acquired?

The datasets were collected from four separate sites spanning Norway (University of Oslo), the Netherlands (Leiden University), and the United States (NIMH and University of Pittsburgh).

Source: Structural brain development between childhood and adulthood: Convergence across four longitudinal samples · DOI · quote verified

What were the magnetic field strengths of the MRI scanners used across the four different sites?

Two samples (CPB and NCD) were scanned using 1.5-T MRI machines, and two samples (Pittsburgh and Braintime) were scanned using 3-T MRI machines.

Source: Structural brain development between childhood and adulthood: Convergence across four longitudinal samples · DOI · quote verified

Which software suite and version was used for the automated MRI image analysis and cortical reconstruction across all datasets?

MRI processing was performed with the FreeSurfer 5.3 image analysis suite, utilizing its longitudinal stream.

Source: Structural brain development between childhood and adulthood: Convergence across four longitudinal samples · DOI · quote verified

Why did the researchers process, quality-control, and analyze all four datasets using identical software and methods?

Standardizing these steps allowed the authors to control for potential confounds introduced by variations in automated software or quality control procedures, helping isolate genuine sample differences.

Source: Structural brain development between childhood and adulthood: Convergence across four longitudinal samples · DOI · quote verified

How was the intracranial volume (ICV) measure extracted for this study, given the assumptions of FreeSurfer's longitudinal pipeline?

Since FreeSurfer's longitudinal pipeline assumes a constant ICV by averaging it across all timepoints, ICV was extracted from the cross-sectional pipeline before longitudinal processing.

Source: Structural brain development between childhood and adulthood: Convergence across four longitudinal samples · DOI · quote verified

Which statistical modeling framework was used to analyze the longitudinal trajectories of brain volumes while handling within-person variation?

The authors used mixed-effects modeling, which estimates fixed effects of variables on volume change while incorporating longitudinal within-person variation as nested random effects.

Source: Structural brain development between childhood and adulthood: Convergence across four longitudinal samples · DOI · quote verified

Why did the authors choose to assess polynomial age models rather than spline modeling?

They selected polynomial models to remain compatible with previous developmental trajectory literature and to allow for a more straightforward interpretation of model comparisons.

Source: Structural brain development between childhood and adulthood: Convergence across four longitudinal samples · DOI · quote verified

How were the different age polynomial models (linear, quadratic, cubic) compared to determine the best-fit model?

Models were compared using likelihood ratio tests and the Akaike Information Criterion (AIC), selecting the model with the lowest AIC that was significantly better than simpler models.

Source: Structural brain development between childhood and adulthood: Convergence across four longitudinal samples · DOI · quote verified

What were the key findings regarding the developmental trajectory of raw Intracranial Volume (ICV) from late childhood to early adulthood?

ICV showed a ~1% annual increase between late childhood and mid-adolescence, and began to stabilize in late adolescence.

Source: Structural brain development between childhood and adulthood: Convergence across four longitudinal samples · DOI

How did the raw developmental trajectory of Whole Brain Volume (WBV) compare to Intracranial Volume (ICV)?

WBV followed a distinct trajectory from ICV, showing a decrease across adolescence and stabilizing in the early twenties, indicating that they continue to change dynamically and should not be treated interchangeably.

Source: Structural brain development between childhood and adulthood: Convergence across four longitudinal samples · DOI · quote verified

What developmental trajectory did Cortical Grey Matter Volume (CGMV) exhibit across the four samples?

CGMV was highest in childhood (~8 years), decreased throughout the second decade (adolescence), and began to stabilize in the third decade.

Source: Structural brain development between childhood and adulthood: Convergence across four longitudinal samples · DOI · quote verified

What was the general trajectory of Cerebral White Matter Volume (CWMV) from late childhood to early adulthood?

CWMV increased between late childhood and mid-adolescence, followed by relative stabilization beginning in mid-to-late adolescence.

Source: Structural brain development between childhood and adulthood: Convergence across four longitudinal samples · DOI · quote verified

What difference in raw Cerebral White Matter Volume (CWMV) size was observed between the US and European samples?

Raw CWMV was generally smaller in the two US samples (CPB and Pittsburgh) compared to the two European samples (Braintime and NCD).

Source: Structural brain development between childhood and adulthood: Convergence across four longitudinal samples · DOI

How is the proportional method defined when controlling for global cranial or brain size?

The proportional method involves dividing the regional brain volume of interest by the global metric (ICV or WBV) to produce a proportional ratio value.

Source: Structural brain development between childhood and adulthood: Convergence across four longitudinal samples · DOI · quote verified

How is the covariate method defined when controlling for global cranial or brain size?

The covariate method includes the global metric (ICV or WBV) as a fixed covariate in statistical regression to account for shared variance.

Source: Structural brain development between childhood and adulthood: Convergence across four longitudinal samples · DOI · quote verified

How did adjusting Cortical Grey Matter Volume (CGMV) using the proportional method affect its developmental curves?

It narrowed confidence intervals and removed the apparent stability of CGMV in late childhood; adjusting by ICV amplified the developmental changes, whereas adjusting by WBV attenuated them.

Source: Structural brain development between childhood and adulthood: Convergence across four longitudinal samples · DOI · quote verified

How did CWMV proportional trajectories differ depending on whether ICV or WBV was used as the denominator?

Adjusting CWMV by ICV flattened the developmental trajectories considerably, whereas adjusting it by WBV made the trajectories more pronounced, extending the period of volume increase.

Source: Structural brain development between childhood and adulthood: Convergence across four longitudinal samples · DOI · quote verified

What happened to CWMV differences between US and European cohorts when adjusting by WBV using the proportional method?

The models for the US samples overlapped, as did the models for the European samples, showing that this method can control for population factors unrelated to brain development.

Source: Structural brain development between childhood and adulthood: Convergence across four longitudinal samples · DOI · quote verified

How did the inclusion of ICV or WBV as a covariate impact the modeled developmental changes of CGMV?

Similar to the proportional method, including ICV as a covariate amplified the developmental changes in CGMV, whereas including WBV as a covariate attenuated these changes.

Source: Structural brain development between childhood and adulthood: Convergence across four longitudinal samples · DOI · quote verified

What were the effects of including ICV versus WBV as a covariate on CWMV developmental models?

Including ICV as a covariate linearized and heavily attenuated CWMV developmental changes, while including WBV as a covariate preserved the nonlinear growth trajectory similar to proportional methods.

Source: Structural brain development between childhood and adulthood: Convergence across four longitudinal samples · DOI · quote verified

What did the models of raw brain volumes (ICV, WBV, CGMV, CWMV) reveal regarding sex differences across the studied age ranges?

Adding sex as a fixed term improved model fit for all raw volumes across samples, indicating that males and females have significant overall size differences in these raw measures.

Source: Structural brain development between childhood and adulthood: Convergence across four longitudinal samples · DOI · quote verified

What was the effect of adding sex to models using the proportional method of brain size adjustment?

Adding sex did not improve the model fit for any of the proportional volumes, indicating that the proportional method removes the main effect of sex from developmental trajectories.

Source: Structural brain development between childhood and adulthood: Convergence across four longitudinal samples · DOI

How did the choice of ICV versus WBV as a covariate affect whether sex differences were detected in CGMV and CWMV?

Adding sex improved model fits when ICV was used as a covariate, but not when WBV was used as a covariate, indicating that WBV covariates absorb sex-related variance in brain size.

Source: Structural brain development between childhood and adulthood: Convergence across four longitudinal samples · DOI · quote verified

Why did the Braintime (Netherlands) and NCD (Norway) samples exhibit larger average ICV than the US samples?

This difference likely reflects population-level differences in average physical height, since Dutch and Norwegian populations are among the tallest globally.

Source: Structural brain development between childhood and adulthood: Convergence across four longitudinal samples · DOI · quote verified

How do the study's findings on Cortical Grey Matter Volume (CGMV) challenge the popular "pubertal peak" narrative of brain development?

The study showed CGMV is highest in childhood (~8 years) and decreases continuously through adolescence, contradicting the narrative that CGMV peaks around the onset of puberty.

Source: Structural brain development between childhood and adulthood: Convergence across four longitudinal samples · DOI · quote verified

What non-synaptic histological processes are thought to contribute to the observed reduction in CGMV measurements during adolescence?

The encroachment of subcortical white matter and continued intracortical myelination alter MR signal intensity and contrast, affecting surface boundary placements.

Source: Structural brain development between childhood and adulthood: Convergence across four longitudinal samples · DOI · quote verified

How did the stabilization timing of CWMV in this study differ from some previous reports?

This study observed CWMV stabilizing by mid-to-late adolescence, whereas some prior literature reported continued white matter increases throughout the second decade of life.

Source: Structural brain development between childhood and adulthood: Convergence across four longitudinal samples · DOI · quote verified

Why do the authors recommend assessing allometric scaling rules before applying size corrections?

Different brain tissues and regions grow at different rates across development, meaning that structural measures do not scale linearly with global size metrics.

Source: Structural brain development between childhood and adulthood: Convergence across four longitudinal samples · DOI · quote verified

Why might Whole Brain Volume (WBV) be a more viable correction measure than Intracranial Volume (ICV) in developmental studies?

Correcting with WBV resulted in more similar developmental trajectories and overall sizes across samples, and WBV may be less susceptible to systematic errors than ICV.

Source: Structural brain development between childhood and adulthood: Convergence across four longitudinal samples · DOI · quote verified

What vulnerability of the proportional method regarding systematic error was discussed?

The proportional method is highly sensitive to systematic errors in ICV values, which can drastically alter calculated volumes, unlike the covariate method.

Source: Structural brain development between childhood and adulthood: Convergence across four longitudinal samples · DOI

What three recommendations do the authors make for future studies that perform cranial or brain size corrections?

Researchers should: 1) demonstrate how the global control variable relates to the regional outcome; 2) provide a clear rationale for the correction technique; and 3) present the uncorrected raw results.

Source: Structural brain development between childhood and adulthood: Convergence across four longitudinal samples · DOI · quote verified

How does the age range of a sample limit the interpretation of best-fitting polynomial models?

The sampled age range heavily influences the selected best-fit model (e.g., producing linear models for narrower ranges like Pittsburgh's) and makes comparing the type of model fit across samples less meaningful.

Source: Structural brain development between childhood and adulthood: Convergence across four longitudinal samples · DOI · quote verified

Why should researchers be cautious when interpreting the timing of peaks and end-point predictions in quadratic and cubic polynomial models?

Global polynomial models are substantially affected by irrelevant factors such as the specific age-range sampled, which can skew end-point and peak predictions.

Source: Structural brain development between childhood and adulthood: Convergence across four longitudinal samples · DOI · quote verified

What is a limitation of this study regarding the spatial scale of the analyzed brain structures?

The study focused on gross measures of cortical grey and cerebral white matter volume, meaning future studies are needed to see how these size-correction findings apply to finer regional or subcortical structures.

Source: Structural brain development between childhood and adulthood: Convergence across four longitudinal samples · DOI