Your brain expands and shrinks over time: These charts show how news and research
When neuroscientist Jakob Seidlitz took his 15-month-old son to the pediatrician for a check-up last week, he left and felt dissatisfied. There was nothing wrong with his son – the youngster seemed to be developing at a typical rate, according to height and weight charts used by the doctor. What Seidlitz felt was missing was a similar measure to measure how his son’s brain grew. “It’s shocking how little biological information doctors have about this critical organ,” said Seidlitz, who is based at the University of Pennsylvania in Philadelphia.
Soon maybe he can change that. In collaboration with colleagues, Seidlitz has amassed more than 120,000 brain scans – the largest collection of its kind – to create the first comprehensive growth charts for brain development. The diagrams visually show how human brains expand rapidly early in life and then shrink slowly with age. Extent of the study, published in Nature April 6 has astonished neuroscientists, who have long had problems with reproducibility in their research, in part due to small sample sizes. Magnetic resonance imaging (MRI) is expensive, which means that researchers are often limited in the number of participants they can register for experiments.
“The sheer amount of data they collect is extremely impressive and really sets a new standard for the field,” said Angela Laird, a cognitive neuroscientist at Florida International University in Miami.
Nevertheless, the authors warn that their database is not completely inclusive – they fought to collect brain scans from all regions of the world. The resulting charts, they say, are therefore only a first draft, and further adjustments would be needed to distribute them in clinical settings.
If the charts are eventually rolled out to pediatricians, great care will be needed to ensure they are not misinterpreted, says Hannah Tully, a pediatric neurologist at the University of Washington in Seattle. “A large brain is not necessarily a well-functioning brain,” she says.
No easy task
Because the structure of the brain varies considerably from person to person, researchers had to collect a large number of scans to create an authoritative set of growth charts with statistical significance. It is not an easy task, says Richard Bethlehem, a neuroscientist at the University of Cambridge, UK, and co-author of the study. Instead of running thousands of scans themselves, which would take decades and be prohibitively costly, the researchers turned to already completed neuroimaging studies.
Bethlehem and Seidlitz sent emails to researchers around the world asking if they would share their neuroimaging data for the project. The duo were amazed at the number of responses they attribute to the covid-19 pandemic, which gives researchers less time in their labs and more time than usual with their email baskets.
In total, the team collected 123,894 MRI scans from 101,457 people, who went from fetus 16 weeks after conception to 100-year-old adults. The scans included brains from neurotypical individuals, as well as individuals 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, regardless of the type of MRI device that had been used.
The end result is a set of diagrams that plot several important brain measurements by age. Some measurement values, such as volume of gray matter and mean bark thickness (width of the gray matter) reach their peak early in a person’s development, while the volume of white matter (found deeper in the brain) tends to reach its peak at the age of 30 (see ‘Brain change ‘). Data on ventricular volume (the amount of cerebrospinal fluid in the brain), in particular, surprised Bethlehem. Researchers knew that this volume increases with age, as it is usually associated with brain atrophy, but Bethlehem was shocked at how fast it tends to grow in late adulthood.
A first draft
The study comes in the heels of a bomb shell published in Nature March 16 shows that most brain imaging experiments contain too few scans to reliably detect links between brain function and behavior, which means that their conclusions may be incorrect. In view of this finding, Laird expects that the field will move towards adopting a framework similar to that used by Seidlitz and Bethlehem, in order to increase statistical power.
Collecting so many amounts of data is akin to a “diplomatic masterpiece,” says Nico Dosenbach, a neuroscientist at Washington University in St. Louis. Louis, Missouri, co-author of the March 16 study. He says this is the scale that researchers should work on when collecting brain images.
Despite the size of the data set, Seidlitz, Bethlehem and their colleagues acknowledge that their study suffers from a problem that is endemic to neuroimaging studies – a notable lack of diversity. The brain scans they collected come mainly from North America and Europe, and reflect a disproportionate amount of populations who are white, university-aged, urban and affluent. This limits the generalizability of the results, says 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 – which accounts for about 1% of all brain scans used in the study.
Billions of people worldwide do not have access to MRI machines, which makes various brain imaging data difficult to obtain, says Laird. But the authors have not stopped trying. They have launched a website where they plan to update their growth charts in real time when they get more brain scans.
With large amounts of data, great responsibility
Another challenge was deciding how to give proper credit to the owners of the brain scans used to construct the charts. Some of the scans came from open-access data sets, but others were closed to researchers. Most of the closed data scans had not yet been processed in a way that would allow them to be incorporated into the growth charts, so their owners did extra work to share them. These researchers were then named as the authors of the thesis.
At the same time, the owners of the open data volumes received only one quote in the journal – which does not have as much prestige for researchers seeking funding, collaborations and promotion. Seidlitz, Bethlehem, and their colleagues processed this data. In most cases, Bethlehem says that in principle there was no direct contact with the owners of these data sets. The magazine lists about 200 authors and cites the work of hundreds of others who have contributed brain scans.
There are a number of reasons why data volumes can be shut down: for example, to protect the privacy of health data or because researchers do not have the resources to publish them. But this does not make it fair that the researchers who opened their data sets did not get authorship, the authors say. In their thesis supplementary information, they argue that the situation “perversely deters open science, because the people who do the most to make their data publicly available may be the least likely to deserve recognition.” Bethlehem and Seidlitz argue that guidelines for authorship of journals, including Nature – which states that each author is expected to have made “significant contributions” to, for example, analysis or interpretation of data – is an obstacle. (Natures news team is editorially independent of its publisher.)
A Nature The spokesperson replied that the question “was carefully considered by the editors and authors in accordance with our authorship policy” and that “all data sets were appropriately credited in accordance with our data citation policy”.
Ultimately, these fears can be traced back to how researchers are evaluated by the scientific firm, says Kaja LeWinn, a social epidemiologist at the University of California, San Francisco, who studies neurodevelopment. She says it is the responsibility of all relevant stakeholders – including funders, journals and research institutions – to re-evaluate how brain science can be properly recognized and rewarded, especially as these types of large-scale studies become more common.
This article is reproduced with permission and was not published until April 6, 2022.