Resting state functional connectivity in relapsing remitting multiple sclerosis with mild disability – a data driven, whole brain multi-voxel pattern analysis study

Background Multivoxel pattern analysis (MVPA) has emerged as a powerful unbiased approach for generating seed regions of interest (ROIs) in resting-state functional connectivity (RSFC) analysis in a data-driven manner. Studies exploring RSFC in multiple sclerosis have produced diverse and often incongruent results. Objectives The aim of the present study was to investigate RSFC differences between persons with relapsing-remitting multiple sclerosis (RRMS) and healthy controls (HC). Methods We performed a whole-brain connectome-wide MVPA in 50 RRMS patients with expanded disability status scale ≤4 and 50 age and gender-matched HCs. Results Significant group differences were noted in RSFC in three clusters distributed in the following regions; anterior cingulate gyrus, right middle frontal gyrus, and frontal medial cortex. Whole-brain seed-to-voxel RSFC characterization of these clusters as seed ROIs revealed network-specific abnormalities, specifically in the anterior cingulate cortex and the default mode network. Conclusions The network-wide RSFC abnormalities we report agree with the previous findings in RRMS, the cognitive and clinical implications of which are discussed herein. IMPACT STATEMENT This study investigated resting state functional connectivity (RSFC) in relapsing remitting multiple sclerosis (RRMS) persons with mild disability (expanded disability status scale ≤4). Whole-brain connectome-wide multivoxel pattern analysis (MVPA) was used for assessing RSFC. Compared to healthy controls (HC), we were able to identify three regions of interest for significant differences in connectivity patterns, which were then extracted as a mask for whole-brain seed-to-voxel analysis. A reduced connectivity was noted in the RRMS group, particularly in the anterior cingulate cortex and the default mode network regions, providing insights into the RSFC abnormalities in RRMS. ### Competing Interest Statement The authors have declared no competing interest.