Multiple Sclerosis (MS) is a disease that causes neuroinflammation and neurodegeneration in central nervous system. Neuroimaging techniques may enable us to better understand the neuropathological mechanisms of MS and how the brain may compensate the pathological changes. We identified the recurring dynamic brain states using fMRI data and investigated the energy required for the transition between those states using the network control theory approach. Our main findings are the dynamic states were visual, somatomotor, and frontoparietal states and the transition energy averaged over all transitions was significantly greater in the MS patients with disability compared to those without disability.
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