Abstract #2138
Effect of noise regression on ASL based functional connectivity
Kay Jann 1 , Edgar A Rios Piedra 1 , Robert X Smith 1 , and Danny JJ Wang 1
1
Department of Neurology, University of
California Los Angeles, Los Angeles, California, United
States
Noise-regression in BOLD-fMRI is necessary to minimize
influences of motion, heart rate and respiration on
functional connectivity (FC). Recently, modern
pseudo-continuous ASL (pCASL) sequences have been shown
to provide comparable FC networks as BOLD. However, the
influence of head motion and physiological noise on
ASL-FC has not yet been investigated. Here we report
effects of different noise-regression strategies on FC
using 2D-EPI and 3D-BS-GRASE pCASL. We found that ASL-FC
analyses are feasible especially for 3D-BS-GRASE pCASL,
but proper noise regression is still mandatory to
prevent erroneous findings related to motion or
physiological noise.
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