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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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