A report published in the current issue of Science details the work of Dr. Dosenbach (Department of Neurology, Washington University School of Medicine) and colleagues in using fMRI to predict individual brain maturation. The researchers developed a functional connectivity multivariate pattern analysis (fcMVPA) approach by applying multivariate pattern analysis (MVPA) to resting-state functional connectivity MRI (rs-fcMRI), typically collected to assess the correlations of spontaneous activity in various brain regions. Application of this methodology to data collected from healthy volunteers allowed the researchers to construct a “brain maturation curve”, establishing an index score for brain maturation analogous to height-weight curves used by pediatricians. The group hopes that this study, by establishing normative index values for brain maturation, will support future studies in pathologies traditionally considered to have equivocal findings on standard MRI protocols – e.g., autism or ADHD.
More from Washington University in St. Louis:
“Pediatricians regularly plot where their patients are in terms of height, weight and other measures, and then match these up to standardized curves that track typical developmental pathways,” says senior author Bradley Schlaggar, MD, PhD, a Washington University pediatric neurologist. “When the patient deviates too strongly from the standardized ranges or veers suddenly from one developmental path to another, the physician knows there’s a need to start asking why.”
Dosenbach used data from five-minute MRI scans of 238 normal subjects ranging in age from 7 to 30. The support vector machine analyzed approximately 13,000 functional brain connections and selected the best 200 to produce a single index of the maturity of each subject. The data allowed scientists to predict whether subjects were children or adults, and roughly formed a curving line that tracks the path of normal functional brain development.
“The beauty of this approach is that it lets you ask what’s different in the way that children with autism, for example, are off the normal development curve versus the way children with attention-deficit disorder are off that curve,” Schlaggar says.
Press release: Mental maturity scan tracks brain development…
Article in Science: Prediction of Individual Brain Maturity Using fMRI…