Abstract #2665
Structural Brain Network Augmentation via Kirchhoffs Laws
Iman Aganj 1 , Gautam Prasad 2 , Priti Srinivasan 1 , Anastasia Yendiki 1 , Paul M. Thompson 2,3 , and Bruce Fischl 1,4
1
Martinos Center for Biomedical Imaging,
Radiology Department, Massachusetts General Hospital,
Harvard Medical School, Boston, MA, United States,
2
Imaging
Genetics Center, Institute for Neuroimaging and
Informatics, University of Southern California, Los
Angeles, CA, United States,
3
Depts.
of Neurology, Psychiatry, Engineering, Radiology and
Ophthalmology, University of Southern California, Los
Angeles, CA, United States,
4
Computer
Science and Artificial Intelligence Laboratory,
Massachusetts Institute of Technology, Cambridge, MA,
United States
-Structural brain connectivity computed from
diffusion-weighted MRI tractography is useful in
studying brain structure in health and disease. Current
approaches for computing the structural brain network
consider fiber bundles directly connecting brain
regions, often disregarding indirect pathways relayed
through other regions. Here we take multi-synaptic
connections into account using mathematical tools
developed for the analysis of resistive electrical
circuits. Our results show that such an augmented
network can improve the classification of Alzheimers
disease patients from healthy controls.
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