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Abstract #5537

Predicting Task Activation from Resting State fMRI: A Comparison of Single Band and Multiband EPI Acquisitions

Alexander D. Cohen1, Elizabeth Zakszewski1, and Yang Wang1

1Radiology, Medical College of Wisconsin, Milwaukee, WI, United States

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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