Report

Prediction of Individual Brain Maturity Using fMRI

See allHide authors and affiliations

Science  10 Sep 2010:
Vol. 329, Issue 5997, pp. 1358-1361
DOI: 10.1126/science.1194144

You are currently viewing the figures only.

View Full Text

Log in to view the full text

Log in through your institution

Log in through your institution

This article has a correction. Please see:

  1. Fig. 1

    Functional brain maturation curve. Individual functional brain maturity levels of 238 rs-fcMRI scans (115 females) between the ages of 7 to 30 years. Chronological age is shown on the x axis and the fcMI on the y axis (females pink, males blue). The fit for the Von Bertalanffy’s equation [a•(1 – ebx), r2 = 0.553, permutation test, P < 0.001, AIC weight = 0.3] is shown with a solid black line. The fit for the Pearl-Reed equation [a/(1 + becx), r2 = 0.555, AIC weight = 0.23] is shown with a solid gray line. The 95% prediction limits are shown with dashed lines.

  2. Fig. 2

    fcMVPA connection and region weights. The functional connections driving the SVR brain maturity predictor are displayed on a surface rendering of the brain. The thicknesses of the 156 consensus functional connections scale with their weights. Connections positively correlated with age are shown in orange, whereas connections negatively correlated with age are shown in light green. Also displayed are the 160 ROIs scaled by their weights (1/2 sum of the weights of all the connections to and from that ROI). The ROIs are color-coded according to the adult rs-fcMRI networks (cingulo-opercular, black; frontoparietal, yellow; default, red; sensorimotor, cyan; occipital, green; and cerebellum, dark blue).

  3. Fig. 3

    SVR brain maturity weights by adult rs-fcMRI networks. The sums of all the functional connection weights within each network are shown to the left of the vertical black line. The sums of all the functional connection weights between networks are shown to the right.

Stay Connected to Science