Graph measures to characterize resting state connectomes in MS patients: An EEG-study over two years. Issue 3 (March 2016) - Hardmeier, M.; Hatz, F.; Penner, I.K.; Naegelin, Y.; Schindler, C.; Kappos, L.; Fuhr, P.
Abstract : Objective: To explore network characteristics of functional connectomes in MS patients over time by graph analysis. Methods: 80 RRMS patients (median EDSS: 2.0, IQR: 1.5–3.0) and 44 normal controls had a 256 channel EEG at baseline, years 1 and 2 (MS: n  = 65 and n  = 63, NC: n  = 35). Subjects were assessed by EDSS, SDMT and a fatigue scale (FSMC). Graph measures (normalized cluster coefficient and path length, small-world-index, degree correlation and diversity, efficiency, transitivity) were calculated in theta-, alpha1-, alpha2- and beta-band connectomes based on the phase lag index in signal-space using TAPEEG. Result: Patients had reduced cognitive processing speed (SDMT: 56.2 vs. 63.8, p  < 0.01), higher fatigue (FSMC: 51.9 vs. 33.2, p  < 0.001) without change longitudinally. Alpha2 network configuration was less efficient in MS at baseline ( p  < 0.05 corrected). Alterations in beta-band were evident at all time points (degree diversity, efficiency, transitivity; p  < 0.05), but did not change longitudinally. Furthermore, SDMT was correlated to these measures at year 2 (all rho = 0.3, p  < 0.05). Conclusions: Beta-band graph measures of network efficiency are weakly but consistently altered in MS showing significant correlations to cognitive processing speed at year 2. The small effect size may be due to low disability in the MS group.