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In order to understand the relationship between functional MRI networks and upper-extremity motor disability, metrics that are more specific to motor pathway damage need to be studied. I propose to collect two metrics that are less dependent on visuospatial ability. These include the finger tapping test and central motor conduction time. The finger tapping test is a simple and reliable measure of upper-extremity motor speed. In MS patients, it was shown to be below average in 55\% of patients on the non-dominant and 65\% below average for the non-dominant hand \cite{Zakzanis_2000}. Electrophysiological measures, such as the motor evoked potential (MEP) are used for the diagnosis of MS and as a measure of dysfunction of the corticospinal tract \cite{kallmann2006early}. Increased central motor conduction times (CMCT) are seen in MS patients, which is a result of demyelination from the disease, conduction block, or axonal destruction \cite{fuhr2001evoked}. The motor evoked potential (MEP) and visual evoked potential (VEP) have been shown to be strongly predictive of changes in MS lower motor disability a full 14 years after the initial measurements \cite{schlaeger2012prediction}, with a spearman's rank correlation of $\rho = 0.69$.   In this proposal, I aim to 1) show that the M1-DMN connectivity increases with increasing central motor conduction time and finger tapping speed and 2) to improve on  the effect size of functional connectivity measures in the prediction of upper-extremity motor disability  by focusing on studying  the connectivity between the PMC and the motor network using a dynamic functional connectivity analysis.