The neonatal period, which is defined as the first 28 days after birth, is known to be a crucial stage in the development of the human brain. During this stage, the brain is known to grow significantly in size, with billions of new connections forming between neurons and supporting basic physiological functions.
Researchers at Charité – Universitätsmedizin Berlin, Humboldt-University in Berlin, and other institutes recently carried out a study aimed at further exploring how the human brain’s overall shape and size as well as the dimensions of distinct regions are linked to a newborn’s development and maturity. Their findings, published in Nature Neuroscience, suggest that the brain’s shape is a key marker of development during the neonatal period.
“The goal of our study was to understand the dynamic changes in brain structure that happen during the neonatal period,” Dr. Stephan Krohn, first author of the paper, and Prof. Carsten Finke, senior author, told Medical Xpress. “In particular, we asked how the brain develops its shape—beyond increasing in size. Prior studies in adult brains had shown that such shape characteristics carry important biological information in later life, but the development of brain shape in very early life remains largely unclear.”
Studying the newborn brain beyond its size
Rather than focusing on the size of the newborn brain, as most past studies have, Krohn and his colleagues wanted to examine its shape and complexity (i.e., morphology). Their goal was to determine whether the brain’s shape provides clues about a newborn’s maturity, genetic profile and even their premature birth.
To do this, they analyzed publicly available magnetic resonance imaging (MRI) data collected from almost 800 human newborns as part of the developing Human Connectome Project (dHCP). Employing a mathematical method called fractal analysis, they tried to delineate the shape of the newborns’ brains.
“This approach yields a geometric measure called fractal dimensionality (FD) that describes the shape of a brain region in terms of its structural complexity,” explained Krohn. “For illustration, the cerebral cortex of very young babies is rather smooth and regular, reflected by lower FD values.
“In contrast, the cortex of older infants becomes increasingly irregular with greater folding, resulting in higher FD values. Fractal analysis thus yields a numerical account of brain shape, which we then related to key biological variables such as infant age and genetic factors.”
FD, the measure obtained using this mathematical approach, was found to be a better predictor of infant maturity than measures of brain structure that earlier studies focused on, such as the brain’s size, the thickness of the curvature or the number of folds in the brain. Focusing on brain shape alone, the researchers were able to predict the age of the infants with high accuracy simply by analyzing MRI scans, with a mean error of four days.
“Brain shape predicted the infants’ ages significantly better than brain size,” said Finke. “Moreover, brain shape captured signatures of premature birth that were not detected with brain size.”
Interestingly, Krohn and colleagues found that the brains of infants who were related to each other, such as twins, were more similar in shape than those of unrelated infants. The shape of the brains of identical twins, who share almost 100% of genes, was found to be more similar than those of fraternal twins, who share approximately 50% of genes.
“Based on this relationship, we were able to predict which babies are twin siblings from their brain shapes with high accuracy (~77% overall, ~97% in identical twins), again outperforming all other studied brain measures,” said Krohn. “These results suggest that the early-life formation of brain shape represents a fundamental maturational process in human brain development.”
Approaching early brain development from a new angle
The recent efforts by Krohn and collaborators could open new possibilities for the study of early brain development, as it introduces a promising approach to examining the shape of the brain. In the future, their proposed methods could also be used to study specific neurodevelopmental and psychiatric disorders, as well as the link between brain morphology and genetics.
“One important area for future research concerns the clinical translation of our framework,” added Finke. “In particular, we are currently conducting a series of clinical studies to explore if brain shape analysis can be used to derive diagnostic or prognostic imaging biomarkers.”
The team’s ongoing research could gather new insight that could guide the creation of more reliable tools to diagnose specific disorders and conditions marked by differences in brain development.
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Publication details
Stephan Krohn et al, Fractal analysis of brain shape formation predicts age and genetic similarity in human newborns, Nature Neuroscience (2025). DOI: 10.1038/s41593-025-02107-w
Journal information:
Nature Neuroscience
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