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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