4.8 Article

Prediction of Individual Brain Maturity Using fMRI

Journal

SCIENCE
Volume 329, Issue 5997, Pages 1358-1361

Publisher

AMER ASSOC ADVANCEMENT SCIENCE
DOI: 10.1126/science.1194144

Keywords

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Funding

  1. NIH [NS55582, NS053425, HD057076, NS00169011, NS51281, NS32979, NS41255, NS46424, DA027046]
  2. John Merck Scholars Fund
  3. Burroughs-Wellcome Fund
  4. Dana Foundation
  5. Ogle Family Fund
  6. McDonnell Center
  7. Simons Foundation
  8. American Hearing Research Foundation
  9. Diabetes Research Center at Washington University

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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.

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