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ORIGINAL ARTICLE   Free accessfree

European Journal of Physical and Rehabilitation Medicine 2019 December;55(6):743-53

DOI: 10.23736/S1973-9087.18.05414-X


language: English

Predictive value of electroencephalography connectivity measures for motor training outcome in multiple sclerosis: an observational longitudinal study

Caterina TRAMONTI 1, Laura S. IMPERATORI 2, Chiara FANCIULLACCI 1, Giuseppe LAMOLA 1, Giada LETTIERI 2, Giulio BERNARDI 2, 3, Luca CECCHETTI 2, Emiliano RICCIARDI 2, Carmelo CHISARI 1

1 Unit of Neurorehabilitation, Department of Medical Specialties, University Hospital of Pisa, Pisa, Italy; 2 MoMiLab, IMT School for Advanced Studies Lucca, Lucca, Italy; 3 University Hospital of Pisa, Pisa, Italy

BACKGROUND: Neurophysiological investigations represent powerful tools to shed light on brain plasticity in multiple sclerosis (MS) patients.
AIM: We investigated the relationship between electroencephalography (EEG)-based connectivity, the extent of brain lesions and changes in motor performance after an intensive task-oriented circuit training (TOCT).
DESIGN: Observational longitudinal study.
SETTING: Outpatients training program.
POPULATION: Sixteen MS patients (10F; mean age =51.4 years; range: 27-67; mean disease duration =15.1 years; range: 2-26; mean Expanded Disability Status Scale 4.4; range: 3.5-5.5), were included in our study.
METHODS: MS patients with mild gait impairment were evaluated through functional scales and submitted to TOCT. Resting-state EEG was performed before (T0) and after (T1) rehabilitation. Alpha-band weighted Phase Lag Index (wPLI) and broadband weighted Symbolic Mutual Information (wSMI) connectivity analyses were performed. White matter lesion load was measured using MRI prior to the TOCT. Neurophysiological and structural parameters were then related to behavioral changes.
RESULTS: Dynamic Gait Index significantly improved after TOCT (F(1,14) =13.10, P=0.003). Moreover, the interaction between TOCT and age was observed for changes in Timed Up and Go (TUG) performance (F(1,14) = 7.75, P=0.015), indicating that older patients only benefited in this measure. Regarding the relationship between EEG connectivity and TOCT outcome, we observed positive correlations between changes in TUG and strength (P=0.017) and efficiency (Pone-tail =0.029) of alpha-band wPLI connectivity at T0. Such correlation was mainly driven by antero-posterior regional interactions (P=0.038), rather than by inter-hemispheric connectivity (P=0.089). Moreover, we observed a positive correlation between performance improvements and wSMI connectivity at T1 (P=0.001) as well as the difference between T0 and T1 (P=0.005). Lesion load percentage was not related to functional improvement after TOCT (Pone-tail=0.137).
CONCLUSIONS: Results of the current study demonstrated that baseline alpha-band wPLI connectivity predicts TOCT outcome in MS patients. Moreover, broadband wSMI tracks neural changes that accompany treatment-related variations in motor performance.
CLINICAL REHABILITATION IMPACT: Our findings suggest that EEG-based connectivity measures may represent a potential tool for customizing rehabilitative management of the disease.

KEY WORDS: Multiple sclerosis; Neurophysiology; Electroencephalography; Magnetic resonance imaging; Brain injuries; Biomarkers

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