Accurate age classification of 6 and 12 month-old infants based on resting-state functional connectivity magnetic resonance imaging data.
Bottom Line: Human large-scale functional brain networks are hypothesized to undergo significant changes over development.Results demonstrate significant changes in measures of brain functional organization that coincide with a special period of dramatic change in infant motor, cognitive, and social development.Explorations of the most different correlations used for SVM lead to two different interpretations about functional connections that support 6 versus 12-month age categorization.
Affiliation: Washington University School of Medicine in St. Louis, 660 South Euclid Avenue, St. Louis, MO 63110, United States. Electronic address: firstname.lastname@example.org.Show MeSH
Mentions: Because SVM was unable to classify risk at each age, groups were then collapsed across risk, resulting in two larger groups for classifying age (n = 128 total datasets; n = 64 datasets/group). Here, SVM classification of 6- versus 12-month-olds was = 89.8% accurate, sensitivity = 92.2%, specificity = 87.5%, p < 2.2251e-308. The 100% consensus features for the classification vector for this run is visualized in Fig. 2 (see also Supplementary Table 3), which illustrates contributions to classification accuracy from 146 functional connections between ROIs which in adults would populate 12 of the 14 networks from Power et al. (2011) and also two ROIs taken from an ASD functional imaging activation likelihood estimation meta-analysis (Philip et al., 2012). The mean Euclidean distance for 12-month-contributing features (green lines) is 72.8 ± 4.0 mm in stereotaxic space, and that for the 6-month-contributing features (orange lines) is 65.9 ± 3.2 mm [t(122.2603) = −1.331; p = 0.186].
Affiliation: Washington University School of Medicine in St. Louis, 660 South Euclid Avenue, St. Louis, MO 63110, United States. Electronic address: email@example.com.