A fundamental problem with fMRI measurements is the strong presence of low frequency systemic physiological noise (<0.15 Hz), which significantly corrupts detection power for hemodynamic variations caused by task induced neuronal activation. In this study, we propose a novel noise removal strategy for task-fMRI studies by taking into consideration a relatively new established property of systemic low frequency oscillations (sLFOs): their dynamic propagation within cerebral vasculature causing voxel-specific arrival delays. We compare the performance of dynamic noise modelling regressors obtained from i) BOLD data and ii) a fingertip HBO signal of non-neuronal origin concurrently recorded with near infrared spectroscopy (NIRS).
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