We propose a novel method for neurodevelopmental brain mapping that displays how an individual's values for a quantity of interest compare with age-specific norms. By estimating smoothly age-varying distributions at a set of brain regions of interest, we derive age-dependent region-wise quantile ranks for a given individual, which can be presented in the form of a brain map. Such quantile rank maps could potentially be used for clinical screening. Bootstrap-based confidence intervals are proposed for the quantile rank estimates. We also propose a recalibrated Kolmogorov-Smirnov test for detecting group differences in the age-varying distribution. This test is shown to be more robust to model misspecification than a linear regression-based test. The proposed methods are applied to brain imaging data from the Nathan Kline Institute Rockland Sample and from the Autism Brain Imaging Data Exchange (ABIDE) sample.
Bibliographical noteFunding Information:
The authors thank Adriana Di Martino and Chao-Gan Yan for preparing the ABIDE fMRI data. The work of Philip Reiss, Clare Kelly and Huaihou Chen is supported by National Institutes of Health grant 1R01MH095836-01A1 . Clare Kelly and F. Xavier Castellanos are supported by National Institutes of Health grant R33MH086952 . Xi-Nian Zuo acknowledges the Hundred Talents Program and the Key Research Program ( KSZD-EW-TZ-002 ) of the Chinese Academy of Sciences , and the Major Joint Fund for International Cooperation and Exchange of the National Natural Science Foundation of China ( 81220108014 , XNZ).
© 2015 Elsevier Inc.
- Box-Cox transformation
- Generalized additive models for location, scale and shape
- Penalized B-splines
- Quantile rank map
- Resting-state fMRI
ASJC Scopus subject areas
- Cognitive Neuroscience