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Abstract #3502

Functional Coherence Index for FMRI Network Analysis Using K-Means Cluster

David Matthew Carpenter1, Emily Eaves1, Johnny Ng1, David H. Schroeder2, Chris A. Condon2, Daniel David Samber1, Richard Haier3, Cheuk Ying Tang4

1Radiology, Mt. Sinai School of Medicine, New York, NY, United States; 2Johnson OConnor Research Foundation, Chicago, Il, United States; 3School of Medicine (Emeritus), UC Irvine, Irvine, Ca, United States; 4Radiology & Psychiatry, Mt. Sinai School of Medicine, New York, NY, United States

There is no standard metric for the integrity of a functional network but such a measure is necessary for quantitatively comparing networks between subjects and groups. The k-means clustering algorithm can be used to segment fMRI data into functional networks or clusters in a very fast and efficient way. In this abstract we present an index for quantifying the overall functional coherence of a network.