2014 Project Week:BrainAging

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  Brain regions with connectivity predictive of effective brain age

Key Investigators

Andrei Irimia, PhD (Institute for Neuroimaging and Informatics, University of Southern California)

John D. Van Horn, PhD (Institute for Neuroimaging and Informatics, University of Southern California)

Project Description

Objective

• Brain connectivity loss due to traumatic brain injury, stroke or multiple sclerosis can have serious consequences on life quality and a measurable impact upon neural and cognitive function.
• Though brain network properties are known to be affected disproportionately by traumatic brain injury to certain gray matter regions, the manner in which white matter insults affect such properties remains poorly understood
• In this project, we seek to combine network-theoretic analysis with 3D Slicer analysis in order to identify the subset of macroscopic neural connections in the adult human brain which are particularly sensitive to network lesioning

Approach, Plan

• we intend to implement systematic lesion analysis of brain connectivity matrices obtained from diffusion neuroimaging over a large sample (N=110) and processed using 3D Slicer
• MRI and DTI volumes will be co-registered in 3D Slicer before further analysis
• connectivity matrices will be computed, pooled across subjects and averaged to compute probabilistic connectivity values
• Slicer will be used to record the average length of the fibers connecting every pair of brain regions
• the average fractional anisotropy (FA) of each fiber line as reconstructed via tractography in Slicer will be recorded

Progress

• we have used 3D Slicer to assist the analysis of TBI effects upon brain connectivity
• we found that certain portions of the paracentral lobule and