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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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