INTRODUCTION
Dynamic functional connectivity (dFC) allows capturing recurring patterns (states) of interaction among functional networks. Here, we investigated resting state (RS) dFC abnormalities across the different clinical phenotypes of multiple sclerosis (MS) and assessed their correlation with motor and cognitive performances.
METHODS
RS fMRI and 3D T1-weighted MRI data were acquired from 128 MS patients (69 relapsing-remitting [RR] MS, 34 secondary progressive [SP] MS, 25 primary progressive [PP] MS) and 40 healthy controls (HC). RS fMRI data underwent independent component analysis and sliding-window correlations, to identify recurring dFC states and between-group dFC differences in the main networks.
RESULTS
DFC identified three recurring connectivity states: State 1 (frequency of appearance during fMRI acquisition=57%, low dFC strength), State 2 (frequency=19%, middle-high dFC strength) and State 3 (frequency=24%, high sensorimotor and visual dFC strength). Compared to HC, MS (as a whole), RRMS and PPMS patients exhibited lower State1/State 3 dFC (p=0.0001, corrected) between sensorimotor, cerebellar and cognitive networks, and some dFC increments (p=range 0.001-0.05, uncorrected) in sensorimotor, visual, default-mode and frontal/attention networks in States 2 and 3. Similar results were observed in SPMS vs RRMS patients. In MS, dFC decrease in sensorimotor, default-mode and frontal/attention networks were correlated with worse motor and cognitive performances.
CONCLUSIONS
MS patients exhibited overall lower dFC, and marginally higher dFC in sensorimotor/cognitive networks in the less-frequent middle/high-connected States. DFC abnormalities became more severe in progressive MS and correlated with motor and cognitive impairment, suggesting the presence of maladaptive mechanisms concomitant with accumulation of damage.