Quantile rank maps: A new tool for understanding individual brain development

Huaihou Chen, Clare Kelly, F. Xavier Castellanos, Ye He, Xi Nian Zuo, Philip T. Reiss

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish
Pages (from-to)454-463
Number of pages10
JournalNeuroImage
Volume111
DOIs
StatePublished - 1 May 2015
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2015 Elsevier Inc.

Keywords

  • Box-Cox transformation
  • Generalized additive models for location, scale and shape
  • MRI
  • Penalized B-splines
  • Quantile rank map
  • Resting-state fMRI

ASJC Scopus subject areas

  • Neurology
  • Cognitive Neuroscience

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