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Evaluating the effects of systemic low frequency oscillations measured in the periphery on the independent component analysis results of resting state networks
2013
NeuroImage
Independent component analysis (ICA) is widely used in resting state functional connectivity studies. ICA is a data-driven method, which uses no a priori anatomical or functional assumptions. However, as a result, it still relies on the user to distinguish the independent components (ICs) corresponding to neuronal activation, peripherally originating signals (without directly attributable neuronal origin, such as respiration, cardiac pulsation and Mayer wave), and acquisition artifacts. In this
doi:10.1016/j.neuroimage.2013.03.019
pmid:23523805
pmcid:PMC3652630
fatcat:gkei7jrglvcarotjfhndgz3wfq