H. Park, R. Bhagalia, C. R. Meyer, B. Kim Department of Radiology, University of Michigan, Ann Arbor, MI, United States, Department of Electric Engineering and Computer Science, University of Michigan, Ann Arbor, MI, United States Introduction: Subject motion is a major source of localization error in fMRI studies. Generally used fMRI analysis methods employ volume alignment of EPI with the assumption that there is no motion between slice acquisitions [1]. In practice, neighboring slices have significantly different motion trajectories in the reference frame of the magnetic field. A motion correction scheme that accounts for interslice motion, in-plane or out-of-plane, by retrospectively mapping each EPI slice into a 3D reference anatomical volume, map-slice-to-volume (MSV), has been in use for fMRI data analyses [2]. This study investigates a more efficient, joint estimation technique for motion parameters in MSV motion correction. As MSV is driven by mutual information (MI) of an image pair, the joint MSV (JMSV) exploits reliable motion parameters from the information rich, mid-brain slices to improve the registration accuracy in slices with poor information contents, i.e., end cap slices or distorted slices [3]. In JMSV, multiple slices are registered simultaneously with constraints for smoothness in motion. A simulated fMRI time series with a known motion have been processed with JMSV to assess the improvement in accuracy.