Think boys mature faster than girls?  Or vice versa?   Let's go to the MRI!

Researchers at Oregon Health&Science University and Washington University in St. Louis say they can now accurately predict a young person's age simply by taking an MRI brain scan and analyzing it with a numerical model. 

OHSU researcher Damien Fair, Ph.D., and colleagues have been studying development of the brain using functional MRI. Traditional functional MRI allows for brain images to be taken while a person is performing an activity. However, in this instance, the scientists use the method to examine the brain is idle or at rest. Previously, Fair used this information to demonstrate how brains develop throughout life.  In the future, this form of analysis may also play a key role in diagnosing childhood developmental delay, ADHD and autism.

When we are young, says Fair, brain activity is more localized in the brain but as we develop, these connections in the brain become more complex and distributed, much like the way a city's transportation system becomes bigger and more complex as the city grows.

"By utilizing this approach along with complex mathematical analysis, called machine learning, we found that we could create a form of brain development yardstick, or what Dr. Dosenbach calls a maturation index," said Fair, a postdoctoral researcher in psychiatry. "Using this yardstick of sorts, we learned that you could effectively determine the subjects level of brain development." 

The researchers hope that, upon further development, the technology will assist in comparing brain function across populations to assess childhood development during the aging process. For instance, a percentile scale could be developed to gauge brain development much in the way weight and height percentiles are calculated for growing children. Such a tool could highlight individual needs and lead to specific ways of helping individual children. 

Citation: Nico U. F. Dosenbach, Binyam Nardos, Alexander L. Cohen, Damien A. Fair, Jonathan D. Power, Jessica A. Church, Steven M. Nelson, Gagan S. Wig, Alecia C. Vogel, Christina N. Lessov-Schlaggar, Kelly Anne Barnes, Joseph W. Dubis, Eric Feczko, Rebecca S. Coalson, John R. Pruett, Jr., Deanna M. Barch, Steven E. Petersen, and Bradley L. Schlaggar, 'Multivariate pattern analysis of 5-minute brain scans provides a measure of brain maturity' , Science 10 September 2010:Vol. 329. no. 5997, pp. 1358 - 1361 DOI: 10.1126/science.1194144