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The Effects of Global Signal Regression on Estimates of Resting-State Blood Oxygen-Level-Dependent Functional Magnetic Resonance Imaging and Electroencephalogram Vigilance Correlations., , and . Brain Connect., 8 (10): 618-627 (2018)A unified framework for sparse non-negative least squares using multiplicative updates and the non-negative matrix factorization problem., , , , , and . Signal Process., (2018)A Unified Bayesian Framework for Sparse Non-negative Matrix Factorization, , , , , and . (2016)cite arxiv:1604.02181v1.pdfComment: Submitted to IEEE Transactions on Signal Processing.Rectified Gaussian Scale Mixtures and the Sparse Non-Negative Least Squares Problem., , , , and . IEEE Trans. Signal Process., 66 (12): 3124-3139 (2018)Global signal regression acts as a temporal downweighting process in resting-state fMRI., , and . NeuroImage, (2017)The global signal in fMRI: Nuisance or Information?, , and . NeuroImage, (2017)Rectified Gaussian Scale Mixtures and the Sparse Non-Negative Least Squares Problem., , and . CoRR, (2016)Nuisance effects in inter-scan functional connectivity estimates before and after nuisance regression., , and . NeuroImage, (2019)Nuisance effects and the limitations of nuisance regression in dynamic functional connectivity fMRI., , and . NeuroImage, (2019)