Project Summary/Abstract Functional magnetic resonance imaging (fMRI) is widely used to study how the human brain interacts with the world and how regions of the brain function as networks. However, head movement during the experiment – even just a few millimeters – leads to errors in the results. This problem confounds research conclusions and often severely limits studies in populations that are likely to move, such as young children. Previous research on motion in fMRI has shown that simply correcting for the head movement with prospective motion correction of the image encoding is not sufficient to recover artifact-free data and accurate resting-state networks, i.e., the secondary effects of head movement on the fMRI experiment must also be addressed. Hence in this project we will develop comprehensive correction of head motion by developing acquisition and analysis software to measure, understand, and correct the relevant effects of head motion. We will develop MR navigator scanner software to perform real-time measurements of head motion, the B0 environment, and the B1– receive intensity profile and account for these effects prospectively during acquisition, in image reconstruction, and in data analysis. Our aim is to produce acquisition, image reconstruction, and analysis tools that can be easily distributed to researchers to further our understanding of motion artifacts in fMRI and provide stable, high- quality data that allow for accurate assessment of functional networks despite being acquired during head motion.