Exercise interventions have emerged as a promising approach for managing symptoms associated with multiple sclerosis (MS). However, changes in brain function underlying exercise-related improvements in symptoms of MS have not been fully investigated, and in no instances have they been investigated using a graph theory approach. For the first time, the effects of an exercise intervention on functional brain network connectivity were examined using graph theory analyses of resting-state functional MRI (fMRI) data among individuals with relapsing-remitting MS (RRMS).
Resting-state fMRI data were obtained from 10 participants before and after 12 weeks of a speeded walking intervention. Functional connectivity data were preprocessed in Data Processing Assistant for Resting-State fMRI Advanced (DPARSF A version 4.2) and analyzed in GraphVar2.02 to compute global and local graph theory metrics. To examine differences in graph metrics before and after the intervention, one-sample permutation tests were performed.
There were no significant pre to post exercise intervention changes in global metrics. Changes in local metrics (i.e. clustering coefficient, local efficiency, degree centrality and betweenness centrality) were mixed, with both increases and decreases observed.
Following a 12-week speeded walking exercise intervention, there were no significant increases or decreases in global graph metrics and results at the level of local metrics were equivocal in individuals with RRMS. Further research with experimental designs that include baseline and longitudinal follow-up, as well as larger sample sizes, is needed to understand the underlying mechanisms of symptom improvement following exercise in RRMS.

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