The human brain expands and contracts over time: these graphs show how

When neuroscientist Jakob Seidlitz took his 15-month-old son to the pediatrician for a check-up last week, he left feeling dissatisfied. There was nothing wrong with his son: the boy seemed to be developing at a typical pace, according to the height and weight charts that the doctor used. What Seidlitz felt was missing was an equivalent metric to measure how his son's brain was growing. “It's shocking how little biological information doctors have about this critical organ,” said Seidlitz, who works at the University of Pennsylvania in Philadelphia.

Soon, he might be able to change that. Working with colleagues, Seidlitz accumulated more than 120,000 brain scans, the largest collection of its kind, to create the first comprehensive growth charts for brain development. The graphs visually show how human brains expand rapidly in the first years of life and then slowly shrink with age. The sheer magnitude of the study, published in the journal Nature, has stunned neuroscientists, who have long had to deal with problems of reproducibility in their research, in part due to the small size of the samples. Nuclear magnetic resonance imaging (NMR) is expensive, which means that scientists often have a limited number of participants who can sign up for experiments.

“The massive set of data they gathered is extremely impressive and really sets a new standard for the field,” said Angela Laird, a cognitive neuroscientist at Florida International University in Miami. Even so, the authors warn that their database is not completely inclusive: they had difficulty collecting brain scans from all regions of the world. The resulting graphs, they say, are only a first draft, and more adjustments would be needed to implement them in clinical settings.

If graphics are finally implemented for pediatricians, great care will be needed to ensure that they are not misunderstood, according to Hannah Tully, a pediatric neurologist at the University of Washington in Seattle. “A big brain isn't necessarily a well-functioning brain,” he stressed.

No easy task

Because the structure of the brain varies significantly from person to person, the researchers had to add a large number of scans to create an authoritative set of growth graphs with statistical significance. For Richard Bethlehem, a neuroscientist at the University of Cambridge, United Kingdom, and co-author of the study, that is not an easy task. Instead of running thousands of scans themselves, which would take decades and would be prohibitively expensive, the researchers turned to neuroimaging studies already completed.

Bethlehem and Seidlitz sent emails to researchers around the world asking them if they would share their neuroimaging data for the project. The duo were amazed by the number of responses, which they attribute to the COVID-19 pandemic, which gave researchers less time in their labs and more time than usual with their email inboxes.

In total, the team collected 123,894 MRI scans of 101,457 people, ranging from fetuses 16 weeks after conception to adults aged 100 years. The scans included brains of neurotypical people, as well as people with a variety of medical conditions, such as Alzheimer's disease, and neurocognitive differences, including autism spectrum disorder. The researchers used statistical models to extract information from the images and ensure that the scans were directly comparable, no matter what type of MRI machine was used.

The end result is a set of graphs that plot several key brain metrics by age. Some metrics, such as gray matter volume and mean cortical thickness (the width of gray matter) peak early in a person's development, while white matter volume (found deeper in the brain) tends to peak around from the age of 30. Data on ventricular volume (the amount of cerebrospinal fluid in the brain), in particular, surprised Bethlehem. Scientists knew that this volume increases with age, because it is usually associated with brain atrophy, but the expert was surprised by how quickly it tends to grow in late adulthood.

A first draft

The study comes on the heels of an explosive article published in Nature on March 16 that shows that most brain imaging experiments contain too few scans to reliably detect links between brain function and behavior, which means that your conclusions may be incorrect. Given this finding, Laird expects the field to move towards adopting a framework similar to that used by Seidlitz and Bethlehem, to increase statistical power.

Accumulating so many datasets is akin to a “diplomatic masterpiece,” said Nico Dosenbach, a neuroscientist at the University of Washington in St. Louis, Missouri, co-author of the March 16 study. For him this is the scale on which researchers should operate when adding brain images.

Despite the size of the data set, Seidlitz, Bethlehem and their colleagues acknowledge that their study suffers from a problem endemic to neuroimaging studies: a notable lack of diversity. The brain scans they collected come mainly from North America and Europe, and disproportionately reflect populations that are white, college-age, urban and affluent. “This limits the generalization of the findings,” said Sarah-Jayne Blakemore, a cognitive neuroscientist at the University of Cambridge. The study includes only three data sets from South America and one from Africa, accounting for about 1% of all brain scans used in the study.

“Billions of people around the world lack access to MRI machines, making it difficult to obtain various brain imaging data,” Laird warned. But the authors did not stop trying and launched a website where they intend to update their growth charts in real time as they receive more brain scans.

With big data sets, big responsibility

Another challenge was determining how to give proper credit to the owners of the brain scans used to build the graphics. Some of the scans came from open access data sets, but others were closed to researchers. Most scans of closed data had not yet been processed in a way that would allow them to be incorporated into the growth charts, so their owners did some extra work to share them. These scientists were later named as authors of the article.

Meanwhile, the owners of the open data sets received only one mention in the document, which is not as prestigious for researchers seeking funding, collaborations and promotions. Seidlitz, Bethlehem and their colleagues processed this data. In most cases, Bethlehem acknowledged that there was essentially no direct contact with the owners of these datasets. The document lists around 200 authors and cites the work of hundreds of people who contributed to brain scans.

KEEP READING: