Abstract #2053
Multi-Echo Independent Component Analysis (ME-ICA) of High Frequency Resting-State fMRI Data
Valur Olafsson 1 , Prantik Kundu 2 , and Thomas Liu 3
1
Neuroscience Imaging Center, University of
Pittsburgh, Pittsburgh, PA, United States,
2
Dept.
of Radiology, Icahn School of Medicine at Mount Sinai,
New York, NY, United States,
3
Center
for functional MRI, UCSD, La Jolla, CA, United States
The recent emergence of fast simultaneous multi-slice
functional MRI acquisitions has increased interest in
exploring high frequency resting-state networks for
functional connectivity MRI. Although studies have
reported detecting high frequency networks, little has
been done to investigate if the underlying source is
truly BOLD based. Here, we propose to investigate the
occurrence of whole brain high frequency BOLD
resting-state networks, using multi-echo independent
component analysis (ME-ICA) of high-pass filtered
multi-echo simultaneous multi-slice (MESMS) data, which
allows for automatic identification of high frequency
BOLD and non-BOLD networks. We find that BOLD networks
at frequencies higher than 0.2Hz are largely
nonexistent.
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