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Activity Number: 170
Type: Topic Contributed
Date/Time: Monday, August 10, 2015 : 10:30 AM to 12:20 PM
Sponsor: ENAR
Abstract #315728
Title: Statistical Methods for Joint Structural-Functional Connectomes
Author(s): Russell Shinohara*
Companies: University of Pennsylvania
Keywords: imaging statistics ; biostatistics ; MRI
Abstract:

We propose statistical methods for quantifying variability in a population of connectomes using general weighted graphical representations. While graphical models center almost entirely on scalar summaries, little work has been done comprehensively studying populations of graphs in their entirety. To study this, we propose generalized variances for complex objects based on distance statistics. We further develop methods for two-sample testing at the whole connectome and the subnetwork levels. We demonstrate the utility of these methods in a connectomic study of autism spectrum disorders using diffusion tensor imaging and magnetoencephalography.


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