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Dosenbach, Nico U. F.; Nardos, Binyam; Cohen, Alexander L.; Fair, Damien A.; Power, Jonathan D.; Church, Jessica A.; Nelson, Steven M.; Wig, Gagan S.; Vogel, Alecia C.; Lessov-Schlaggar, Christina N.; Barnes, Kelly Anne; Dubis, Joseph W.; Feczko, Eric; Coalson, Rebecca S.; Pruett, John R.; Barch, Deanna M.; Petersen, Steven E.; Schlaggar, Bradley L.
Science (American Association for the Advancement of Science), 09/2010, Letnik: 329, Številka: 5997Journal Article
Group functional connectivity magnetic resonance imaging (fcAARI) 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.
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JCR | SNIP | JCR | SNIP | JCR | SNIP | JCR | SNIP |
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Povezave do osebnih bibliografij avtorjev | Povezave do podatkov o raziskovalcih v sistemu SICRIS |
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Vir: Osebne bibliografije
in: SICRIS
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