| Literature DB >> 20829489 |
Nico U F Dosenbach1, 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, Deanna M Barch, Steven E Petersen, Bradley L Schlaggar.
Abstract
Group functional connectivity magnetic resonance imaging (fcMRI) studies have documented reliable changes in human functional brain maturity over development. Here we show that support vector machine-based multivariate pattern analysis extracts sufficient information from fcMRI data to make accurate predictions about individuals' brain maturity across development. The use of only 5 minutes of resting-state fcMRI data from 238 scans of typically developing volunteers (ages 7 to 30 years) allowed prediction of individual brain maturity as a functional connectivity maturation index. The resultant functional maturation curve accounted for 55% of the sample variance and followed a nonlinear asymptotic growth curve shape. The greatest relative contribution to predicting individual brain maturity was made by the weakening of short-range functional connections between the adult brain's major functional networks.Entities:
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Year: 2010 PMID: 20829489 PMCID: PMC3135376 DOI: 10.1126/science.1194144
Source DB: PubMed Journal: Science ISSN: 0036-8075 Impact factor: 47.728