Prediction of Individual Brain Maturity Using fMRI

Prediction of Individual Brain Maturity Using fMRI

2010 September 10; 329(5997): 1358–1361 | 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 Fezcko, Rebecca S. Coalson, John R. Pruett Jr., Deanna M. Barch, Steven E. Petersen, Bradley L. Schlaggar
This study demonstrates that functional connectivity magnetic resonance imaging (fcMRI) data can be used to predict individual brain maturity across development. Using support vector machine-based multivariate pattern analysis (MVPA) on 5 minutes of resting-state fcMRI data from 238 typically developing volunteers aged 7 to 30 years, the researchers developed a functional connectivity maturation index (fcMI). The fcMI, which accounts for 55% of the sample variance, follows a nonlinear asymptotic growth curve. The prediction of individual brain maturity was primarily driven by the weakening of short-range functional connections between major brain networks. The findings suggest that fcMRI-based methods could aid in diagnosing developmental delays and neuropsychiatric disorders, particularly those without structural brain abnormalities. The study also highlights the importance of functional segregation and integration in brain maturation, with the right anterior prefrontal cortex being the most predictive region.This study demonstrates that functional connectivity magnetic resonance imaging (fcMRI) data can be used to predict individual brain maturity across development. Using support vector machine-based multivariate pattern analysis (MVPA) on 5 minutes of resting-state fcMRI data from 238 typically developing volunteers aged 7 to 30 years, the researchers developed a functional connectivity maturation index (fcMI). The fcMI, which accounts for 55% of the sample variance, follows a nonlinear asymptotic growth curve. The prediction of individual brain maturity was primarily driven by the weakening of short-range functional connections between major brain networks. The findings suggest that fcMRI-based methods could aid in diagnosing developmental delays and neuropsychiatric disorders, particularly those without structural brain abnormalities. The study also highlights the importance of functional segregation and integration in brain maturation, with the right anterior prefrontal cortex being the most predictive region.
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