Larger Lesion Volume in People with Multiple Sclerosis is Associated with Increased Transition Energies Between Brain States and Decreased Entropy of Brain Activity

Abstract The mapping between severity or location of this brain tissue damage and an individual's impairment remains challenging in multiple sclerosis (MS). Network control theory (NCT) can be used to characterize the brain's energetic landscape using an individual's structural connectome and brain activity dynamics. We apply brain activity dynamics analysis and NCT to functional time series and structural connectomes in controls and MS patients with and without disability and compare the three groups' resulting metrics. We also assessed the entropy of the three groups' brain activity time series. NCT was used to compute the energy required to transition between each pair of recurring dynamic brain states which were identified with k-means approach applied on fMRI time series. Larger transition energies were associated with MS patient who had disability compared to controls. Entropy was negatively correlated with lesion volume as was transition energy in MS. Functional compensation of brain activity in MS patients without disability may result in decreased transition energies between states compared to controls, but, as this mechanism diminishes, transition energies increase and disability occurs. Larger volumes of MS-related lesions may result in greater energetic demands to transition between brain states which then leads to lower overall entropy of brain activity.