The human brain undergoes significant development during the final prenatal months and through the first year of life. And while scientists have begun to map the developmental trajectories of this early period, blueprints of healthy development do not yet exist.

In a new study, Yale researchers demonstrate that models of brain age may be useful for tracking healthy brain development and identifying environmental factors that influence the pace of development.

They also reveal that advanced development isn't universally positive.

For the study, published Nov. 26 in Nature Communications, researchers used structural and functional brain images from more than 600 term and preterm infants collected via magnetic resonance imaging (MRI) in the United Kingdom from the Developing Human Connectome Project.

With the images, researchers trained machine learning models to predict an infant's brain age from neuroimaging data.

"Typically, researchers study brain age from either structural or functional imaging data, but here we used both," said Huili Sun, lead author of the study and a Ph.D. candidate in the lab of senior author Dustin Scheinost, associate professor of radiology and biomedical imaging at Yale School of Medicine. "Brain age is a novel concept in terms of taking all of the very high-dimension brain data and summarizing it into a single, but meaningful, number for an individual."

When testing the models, the researchers found they were able to accurately predict infants' ages whether these estimates were based on data from the whole brain or data from particular brain networks.

From there, the researchers investigated brain age gaps—the differences in the actual age of an infant and the age the models predicted them to be based on brain images. These gaps, said the researchers, can serve as an indicator of whether an infant is developing more quickly or slowly than they should be.

"We wanted to understand which type of factors might influence brain age gaps," said Sun. "Since the brain images were collected from infants shortly after birth, many of the environmental factors that might be at play would have had an influence during pregnancy. So we looked at maternal demographics and whether they had any associations with brain age gaps."

Those demographics included maternal age, education, mental health history, physical conditions, and substance use. Maternal age had the strongest association, the researchers found, with higher maternal age associated with more mature structural brain age for term infants.

And while one might assume that an infant's brain being more developed than expected could be a good thing, the researchers found that wasn't always the case.

"We found that while the older a child's brain appeared to be in infancy, the better their cognitive abilities were as toddlers, but their ability to regulate their behaviour and emotions was worse," said Sun. "So there are costs and benefits to advanced development and following the normative trajectory is probably best, according to our findings."

Going forward, the researchers want to investigate brain age trajectory further into infancy and toddlerhood and to better understand what role genetics might play in brain age gaps. Additionally, because the data from this study was collected in Europe, it will be important to conduct similar studies on brain development trajectory in children from different regions and from different cultures, said the researchers.

"Brain age and brain age gaps are a valuable tool for studying neurodevelopment in infants and children," said Sun. "And being able to establish normative trajectories of development in early life will help identify why and when individuals deviate from those trajectories and could point to how and when to intervene."