JSM 2013 Home
Online Program Home
My Program

Abstract Details

Activity Number: 65
Type: Topic Contributed
Date/Time: Sunday, August 4, 2013 : 4:00 PM to 5:50 PM
Sponsor: SSC
Abstract - #309909
Title: Determining Multimodal Biomarkers for Neurodegenerative Diseases
Author(s): DuBois Bowman*+ and Wenqiong Xue
Companies: Emory University and Emory University
Keywords: Imaging ; Bayesian model ; Spatial model ; Prediction ; Parkinson's disease

Despite the considerable progress in understanding the biology of Parkinson's disease (PD), reliable biomarkers are still lacking for early stage detection of PD. Advances in biotechnology have led to studies that collect large-scale, multimodal imaging data sets. Leveraging data from magnetic resonance imaging (MRI), resting-state functional MRI, and diffusion tensor imaging (DTI), we present a statistical framework to identify multimodal PD biomarkers. Specifically, we consider a Bayesian hierarchical model to predict PD using imaging data reflecting both functional and structural properties of the brain. We consider a two-level brain parcellation and assume different spatial correlation structures between voxels within a subregion, between subregions (within a region), and between different regions. We perform Markov Chain Monte Carlo estimation via Gibbs sampler. Our model yields both whole-brain and voxel-level prediction, and we apply leave-one-out cross validation to assess prediction accuracy. We apply our model to our PD data and conduct simulation studies to evaluate its performance.

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

Back to the full JSM 2013 program

2013 JSM Online Program Home

For information, contact jsm@amstat.org or phone (888) 231-3473.

If you have questions about the Continuing Education program, please contact the Education Department.

The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.

ASA Meetings Department  •  732 North Washington Street, Alexandria, VA 22314  •  (703) 684-1221  •  meetings@amstat.org
Copyright © American Statistical Association.