Recent studies have used resting state functional MRI (rs-fMRI) to predict task activation on an individual basis using a linear-regression machine learning technique. Limited existing studies have used either low-resolution single-band (SB) or high-resolution multiband (MB) data and shown promising results. In this study, SB and MB resting state data were acquired in a group of volunteers to compare their ability to predict motor task activation. Our results showed no significant differences between SB- and MB-based motor task predictions. These findings suggest conventional SB scans might be suitable for making predictions regarding task activation in some clinical settings.
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