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Abstract #3579

Quantitative Evaluation of RSN Functional Contrast in Low-TR fMRI

Stephen Smith1, Karla Miller1, Christian Beckmann1,2, Steen Moeller3, Kamil Ugurbil3, Essa Yacoub3, David Feinberg4,5

1FMRIB, Oxford University, Oxford, Oxon, United Kingdom; 2Donders Institute, Radboud University, Nijmegen, Netherlands; 3Center for Magnetic Resonance Research, University of Minnesota Medical School, MN, United States; 4Advanced MRI Technologies, Sebastopol, CA, United States; 5Helen Wills Institute for Neuroscience, UC Berkeley, CA, United States

We present quantitative evaluation of the functional contrast (effective CNR) in low-TR data that has been acquired by combining two different EPI accelerations, generating whole-brain FMRI images as rapidly as 0.4s. We use ICA and multiple-regression to identify ~62 RSNs in each of 3 subjects, and find that, while peak Z-stat is roughly constant across the 3 TRs for single-regression analyses (seed-based correlation), when deriving the functional parcellation through a multiple-regression, the lowest TR data had peak Z-stat increased by 60% and RSN spatial extent increased by 100%, compared with the unaccelerated data.