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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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