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Abstract #3967

Characterization of Whole-brain Dynamic Connectivity Patterns using Simultaneous MultiSlice (SMS) Resting-State fMRI

Hesamoddin Jahanian 1 , Samantha Holdsworth 1 , Thomas Christen 1 , Hua Wu 2 , Kangrong Zhu 3 , Adam Kerr 3 , Matthew J Middione 4 , Robert F Dougherty 2 , Michael Moseley 1 , and Greg Zaharchuk 1

1 Department of Radiology, Stanford University, Stanford, CA, United States, 2 Center for Cognitive and Neurobiological Imaging, Stanford University, Stanford, CA, United States, 3 Department of Electrical Engineering, Stanford University, Stanford, CA, United States, 4 Applied Sciences Laboratory West, GE Healthcare, Menlo Park, CA, United States

In an effort to distinguish cognitive states of the brain from rsfMRI data, we studied the dynamics of the whole-brain functional connectivity using high temporal sampling rate (TR=350 ms) Simultaneous MultiSlice (SMS) Resting-state fMRI. We probed the whole-brain functional connectivity in a wide frequency spectrum over a sliding window (duration:17.5 s, steps:7 s) and further characterized its dynamic changes into distinct connectivity states using k-means clustering.

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