Quantifying the relationship between the brain’s functional activity patterns and its structural backbone is crucial when relating the severity of brain pathology to disability in multiple sclerosis (MS). Network control theory (NCT) characterizes the brain’s energetic landscape using the structural connectome and patterns of brain activity over time. We applied NCT to investigate brain-state dynamics and energy landscapes in controls and people with MS (pwMS). We also computed entropy of brain activity and investigated its association with the dynamic landscape’s transition energy and lesion volume. Brain states were identified by clustering regional brain activity vectors, and NCT was applied to compute the energy required to transition between these brain states. We found that entropy was negatively correlated with lesion volume and transition energy, and that larger transition energies were associated with pwMS with disability. This work supports the notion that shifts in the pattern of brain activity in pwMS without disability results in decreased transition energies compared to controls, but, as this shift evolves over the disease, transition energies increase beyond controls and disability occurs. Our results provide the first evidence in pwMS that larger lesion volumes result in greater transition energy between brain states and decreased entropy of brain activity.

We investigated the brain-state dynamic and energy landscapes in healthy individuals and people with multiple sclerosis (pwMS). We also investigated the entropy of brain activity and its association with transition energy between brain states and lesion volume. We clustered regional brain activity time series to identify the brain states. Then, we applied network control theory using structural connectivity network to identify the minimum required energy to transition between brain states. We observed the pwMS without disability showed decreased transition energy, while pwMS with evidence of disability showed increased transition energy compared to healthy individuals. Lower entropy of brain activity was associated with greater lesion load and larger transition energy. This study provides a possible mechanism of how MS-related damage to the brain’s structural backbone can impact brain dynamics, entropy, and energetics.

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Competing Interests: The authors have declared that no competing interests exist.

Handling Editor: Shella Keilholz

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