Your brain expands and contracts over time — these charts

Neuroscientist Jakob Seidlitz was dissatisfied when he took his 15-month-old son to a pediatrician last week. His son had no problems — the height and weight charts used by the doctor showed the young man growing at a typical pace. Feeling the lack of Seydlitz was an equivalent indicator of how his son’s brain was growing. “It’s shocking how little biological information doctors have about this important organ,” said Seydlitz, based at the University of Pennsylvania in Philadelphia.

Soon he may be able to change that. Working with his colleagues, Seydlitz has accumulated over 120,000 brain scans. This is the largest collection of this kind and created the first comprehensive growth chart for brain development. The chart visually shows how the human brain expands rapidly early in life and then slowly shrinks with age.The full size of the study published in Nature April 6¹Surprised the neuroscientist. For a long time I had to tackle the issue of reproducibility In their study, the small sample size is also a factor. Magnetic resonance imaging (MRI) is expensive. This means that scientists often have a limited number of participants who can enroll in an experiment.

“The vast data sets they have collected are very impressive and actually set new standards in this area,” says Angela Laird, a cognitive neuroscientist at Florida International University in Miami.

Still, the authors warn that the database is not completely comprehensive — they had a hard time collecting brain scans from all parts of the world. Therefore, they say the resulting chart is only the first draft and requires further tweaking to deploy in the clinical setting.

When the charts are finally published to pediatricians, great care must be taken not to misunderstand them, says Hannah Tally, a pediatric neurologist at the University of Washington in Seattle. “The big brain is not always a well-functioning brain,” she says.

No easy task

Because the structure of the brain varies greatly from person to person, researchers needed to aggregate a huge number of scans to create a statistically significant and reliable set of growth charts. It’s not an easy task, says Richard Bethlehem, a neuroscientist and co-author of the study at the University of Cambridge, UK. Instead of performing decades and exorbitantly expensive thousands of scans on their own, researchers turned to already completed neuroimaging studies.

Bethlehem and Seidritz sent an email to researchers around the world asking if they would like to share the neuroimaging data for the project. The duo were amazed at the number of replies resulting from the COVID-19 pandemic, which caused researchers to spend less time in the lab and more time than usual in their email inbox.

In total, the team aggregated 123,894 MRI scans from 101,457 people who performed the entire range from fetuses 16 weeks after conception to adults aged 100 years. The scan included not only the brains of people with typical development, but also people with various medical conditions such as Alzheimer’s disease, and differences in neurocognition, including autism spectrum disorders. Researchers used a statistical model to extract information from the images and found that scans could be compared directly, regardless of the type of MRI machine used.

The final result is a series of charts that plot several major brain metrics by age. Some indicators, such as the amount of gray matter and the average cortical thickness (width of gray matter), peak early in human development, while the amount of white matter (deep in the brain) is around the age of 30. Tends to peak by (see). “Changes in the brain”). In particular, data on ventricular volume (the amount of cerebrospinal fluid in the brain) surprised Bethlehem. Scientists knew that this amount would increase with age, as it is usually associated with cerebral atrophy, but was shocked by the tendency of bethlehem to grow rapidly in late adulthood.

First draft

This study Nature March 16² Most brain imaging experiments Too few scans To reliably detect the link between brain function and behavior. That is, those conclusions may not be correct. In light of this finding, Laird hopes that the field will move towards adopting a framework similar to that used in Seydlitz and Bethlehem to enhance statistical power.

Niko Dosenbach, a neuroscientist at Washington University in St. Louis, Missouri, who co-authored the March 16 study, said collecting so many datasets was like a “masterpiece of diplomacy.” I am saying. He says this is the scale that researchers should manipulate when aggregating images of the brain.

Despite the size of the dataset, Seydlitz, Bethlehem and his colleagues acknowledge that their work suffers from a problem specific to neuroimaging research: a significant lack of diversity. The brain scans they collect are primarily from North America and Europe and disproportionately reflect whites, college days, urban and wealthy people. Sarah Jayne Blakemore, a cognitive neuroscientist at the University of Cambridge, states that this limits the generalization of findings. This survey includes only three datasets from South America and one dataset from Africa. It accounts for about 1% of all brain scans used in the study.

Billions of people around the world do not have access to MRI scans, making it difficult to obtain diverse brain imaging data, Laird said. However, the author did not stop trying.They launched Websites they are trying to update their growth charts In real time as they receive more brain scans.

Big responsibility for big datasets

Another challenge was deciding how to give proper credit to the owner of the brain scan used to create the chart. Some scans were from open access datasets, while others were not open to researchers. Most closed data scans have not yet been processed so that they can be incorporated into growth charts, so owners have done additional work to share them. Later, these scientists were nominated as authors of the dissertation.

On the other hand, the owners of open datasets were only cited in the paper. This is less prestigious for researchers seeking funding, collaboration and promotion. Seydlitz, Bethlehem and his colleagues processed this data. In most cases, Bethlehem states that there was essentially no direct contact with the owners of these datasets. This paper lists about 200 authors and cites the work of hundreds of others who have contributed to brain scans.

There are several reasons why datasets are closed. For example, to protect the privacy of health data, or because researchers do not have the resources to publish the dataset. However, this does not justify that the researcher who opened the dataset did not qualify as an author, the authors say. In the supplementary information in their dissertation, they said, “The situation reverses open science because people who do the most to publish data may be least likely to be recognizable. I blame you. “Bethlehem and Seydlitz advocate author guidelines from journals including: Nature For example, it is an obstacle that each author is expected to make a “substantial contribution” to the analysis and interpretation of the data. ((((NatureThe news team is editorial independent of the publisher. )

A Nature Publicist This issue is answered as “carefully considered by editors and authors according to our author policy” and “all datasets were properly credited according to our data citation policy”.

Ultimately, these concerns can be traced back to how researchers are evaluated by scientific companies, says Kaja LeWinn, a social epidemiologist at the University of California, San Francisco, who studies neurological development. increase. She reassessed how brain science can be properly recognized and rewarded, especially as these types of large-scale studies become more common, funders, journals, It is the duty of all relevant stakeholders, including research institutes.