Online Program Home
My Program

Abstract Details

Activity Number: 421
Type: Topic Contributed
Date/Time: Tuesday, August 2, 2016 : 2:00 PM to 3:50 PM
Sponsor: Section on Nonparametric Statistics
Abstract #319896
Title: Functional Data Analysis for Sparse and Irregular Longitudinal MRI Measurements in the Developing Brain
Author(s): Xiongtao Dai* and Hans-Georg Mueller and Jane-Ling Wang
Companies: Healthy Birth, Growth and Development knowledge integration (HBGDki) Community and University of California at Davis and University of California at Davis
Keywords: correlation ; regression ; child development ; myelin water fraction ; longitudinal data

Longitudinal data on the brain development of children are often extremely sparse and irregular in time, and this applies for example to the MRI brain scan data in the BAMBAM longitudinal children's study. Our analysis aims to quantify the time dynamics of the correlations between myelin water fraction levels for various brain regions that can be computed from the longitudinal MRI brain scans. This requires new functional data analysis methodology that will be introduced and illustrated with these data. Specifically addressing the problem of working with sparse longitudinal measurements, we present a simple approach to construct pairwise correlation functions and apply this to study time-dynamic correlations between brain regions. We also discuss methods to relate sparsely available predictor data to subsequently recorded outcomes and will illustrate this with the prediction of cognitive development scores from sparsely measured myelin water fraction levels.

Authors who are presenting talks have a * after their name.

Back to the full JSM 2016 program

Copyright © American Statistical Association