Functional imaging based on detection of neuronal currents using spin-lock prepared MRI may overcome limitations inherent to haemodynamic fMRI with BOLD. However, in-vivo application is hindered by system imperfections. In this work, the effects of B0 and B1+ inhomogeneities and background noise on neuro-current MRI signals are quantified. Furthermore, a new statistical data-processing technique based on the analysis of signal variability, SVarM, is proposed for neuro-current MRI time series. SVarM achieves overall higher sensitivity than existing data-processing methods and is shown to be more robust in the presence of system imperfections.
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