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\section{Overview}  There is a disconnect between clinical disability in multiple sclerosis (MS) and structural damage seen on MRI, called the clinico-radiological paradox \cite{barkhof2002clinico}. Even though focal white matter lesions seen on MRI largely characterize multiple-sclerosis, lesion volumes are not strongly correlated with clinical motor disability \cite{lesions1,lesions2,lesions3}. Possible reasons for this paradox include lesion location\cite{Charil_2003} and gray matter atrophy \cite{Charil_2007}, however the correlations with disability are modest (r=0.3). Another hypothesis is that functional adaptation plays a role, where brains adapt to the damage caused by MS in order to minimize disability\cite{rocca2012large}. My preliminary results have shown that changes in functional MRI network connections correlate with performance on a complex motor dexterity task, even after accounting for structural damage. However, poor performance on a complex motor task may not be attributable to motor network damage & reorganization alone. For example, damage to the visual pathway involved in a complex task may confound results. Therefore, I propose to study how performance on simpler motor tasks relate to functional network connectivity changes, and develop a functional biomarker to predict motor performance. I intend to measure the central motor conduction time (CMCT), which is sensitive to corticospinal tract damage\cite{udupa2013central}, by measuring motor evoked potentials (MEP) using transcranial magnetic stimulation (TMS). Additionally, finger tapping speed (FT) will be collected on MS patients, which has been shown to be more impaired in MS patients compapred to measures of manual dexterity\cite{Zakzanis_2000}. Functional biomarkers will be developed using a traditional, hypothesis driven approach, followed by a functional dynamic network analysis focused on the posteriomedial cortex. cortex (PMC).  Features of the functional network will be extracted based on CMCT and FT. This will result in a biomarker that reflects the ability of a subject to functionally adapt to MS damage, which could lead to personalized medical treatment of their disease. \subsection*{Specific Aim 1: Develop a functional metric that relates to CMCT and FT  using a hypothesis driven analysis} \subsection*{Specific Aim 2: Build a classifier to predict high/low NHPT group membership or healthy control using a Improve on the prediction of simple and complex motor tasks by developing an fMRI metric based on  dynamic functional connectivity analysis} of the PMC}