Estimation of respiration-induced noise fluctuations from undersampled multislice fMRI data

Abstract

Functional MRI time series data are known to be contaminated by highly structured noise due to physiological fluctuations. Significant components of this noise are at frequencies greater than those critically sampled in standard multislice imaging protocols and are therefore aliased into the activation spectrum, compromising the estimation of functional activations and the determination of their significance. However, in this work it is demonstrated that unaliased noise information is available in multislice data, and can be used to estimate and reduce noise due to high-frequency respiratory-related fluctuations. Magn Reson Med 45:635-644, 2001. Published 2001 Wiley-Liss, Inc.