How does brain development vary from person to person?
While most teenagers show similar patterns of overall brain shrinkage and white matter growth, individuals vary widely in the timing, speed, and direction of these structural changes.
Source
Inter-individual variability in structural brain development from late childhood to young adulthood
Study at a glance
- Design
- Cohort — Three-wave anatomical MRI from BrainTime, NCD, and LunaCog; only participants with three high-quality scans
- N
- N=269 · 149 females, 120 males from Leiden, Oslo, and Pittsburgh
- Population
- Typically developing youth with three longitudinal anatomical scans from late childhood onward
- Outcome
- Inter-individual variability in structural brain-development trajectories
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Inspect source passages
How does brain development vary from person to person?
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269 participants
Only participants with three high-quality anatomical brain scans were included in the present analysis, for a total of 269 participants (149 females, 120 males).
three separate longitudinal datasets
This study examined participants from three separate longitudinal datasets collected from independent research sites located in three countries: Leiden University (BrainTime), University of Oslo (Neurocognitive Development; NCD), and University of Pittsburgh (LunaCog).
What they did
The researchers analyzed data from 269 participants who each received three brain scans over several years. This sample included 149 females and 120 males drawn from three distinct longitudinal datasets. The researchers calculated the yearly percentage change in cortical and subcortical structures to track individual brain growth trajectories.
What they found
The researchers discovered that individuals show significant differences in both the speed and direction of brain changes, particularly during the transition into adolescence and early adulthood. While most adolescents showed a decrease in outer brain thickness and volume, females with larger initial brain measurements showed much faster rates of decline than those with smaller measurements. In contrast, males did not show this relationship between overall brain size and their rate of cortical change. Additionally, most participants showed increases in white matter volume during early adolescence, which then stabilized by their mid-teens.
The limits
What it doesn't show
First, the study lacks sociodemographic data, making it impossible to determine how environmental factors or life experiences might drive these individual brain differences. Second, because participants only had three scans, the study could not map complex, non-linear individual growth trajectories, which typically require four or more scan points. Third, the thresholds used to define true developmental changes are statistical estimates, meaning some reported variations might reflect scan measurement errors rather than actual biological growth. Finally, the study is observational and cannot establish causal links between specific brain structures and behavioral or psychological outcomes.
Key terms
- Longitudinal study
- A research design that involves repeating the same observations or measurements of the same individuals over a period of time.
- Cortical thickness
- The local geometry of the cerebral cortex, representing the depth of the gray matter layer on the outer surface of the brain.
- White matter
- Brain tissue composed of nerve fibers wrapped in myelin, which acts as the communication network connecting different brain regions.
- Subcortical structures
- A group of diverse neural formations located deep within the brain, beneath the cerebral cortex, such as the amygdala and hippocampus.
- Generalized Additive Mixture Model (GAMM)
- A flexible statistical modeling technique that accounts for non-linear relationships and clustered data by combining smooth functions with random effects.
- Annualized percent change
- A metric that quantifies the rate of change in a brain structure per year, adjusted relative to the average size of that structure.
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Quiz yourself
Why are longitudinal datasets necessary compared to cross-sectional datasets for studying individual brain development?
Common questions
Why did this study use longitudinal datasets instead of comparing different age groups?
Cross-sectional studies, which compare different age groups at a single point in time, can only show average age trends. Longitudinal studies track the same individuals over time, which is the only way to measure how much variation exists in how individual brains actually change as they grow.
Do boys and girls show different patterns of brain development as they grow up?
Yes. While both sexes show overall changes, the study found key differences. For instance, girls with larger cortical structures showed faster rates of brain tissue thinning, whereas boys' rate of brain change remained similar regardless of their initial brain size.
What are 'transition periods' and why do they show more variability?
Transition periods occur when children enter adolescence or when young adults enter early adulthood. During these times, individuals vary widely in the timing of their brain development, meaning some people's brains begin maturing earlier or later than their peers.
Does having a thinner brain cortex during adolescence mean someone is more mature?
Not necessarily. Although group averages show that the cortex thins during adolescence, there is vast individual variation. A person with a naturally thinner cortex may not have progressed further in development than someone with a thicker cortex.
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