Online Program Home
My Program

Abstract Details

Activity Number: 630
Type: Invited
Date/Time: Thursday, August 4, 2016 : 8:30 AM to 10:20 AM
Sponsor: WNAR
Abstract #318239 View Presentation
Title: Statistical Methods for Global and Subnetwork Connectomic Analyses
Author(s): Russell Shinohara* and Simon Vandekar
Companies: University of Pennsylvania and University of Pennsylvania
Keywords: connectomics ; imaging ; biostatistics ; kernel ; distance ; network

Connectomics, the comprehensive study of connections in the brain, is crucial for charting normal brain development and for understanding how etiology changes the structural and functional network landscapes. While much effort has centered on statistical methods for connectomic data, most network analyses first decompose the brain into subnetworks and then test for disease or outcome-related differences. Increasingly, kernel and distance-based methods are being employed; however, these methods provide only global and subnetwork-specific tests. In this work, we propose and develop a new framework for kernel testing that allows for optimally powerful testing across brain subnetworks while also identifying which networks or regions are associated with the outcome of interest. We illustrate this methodology using extensive simulations and the analysis of a large cohort of subjects who underwent an extensive neuroimaging protocol.

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

Back to the full JSM 2016 program

Copyright © American Statistical Association