Beta-band oscillations as a biomarker of gait recovery in spinal cord injury patients: A quantitative electroencephalography analysis

Author(s)

Simis, Marcel ^[1] ; Uygur-Kucukseymen, Elif ^{[2, 3, 4]} ; Pacheco-Barrios, Kevin ^{[2, 3, 4, 5]} ; Battistella, Linamara R. ^[1] ; Fregni, Felipe ^{[2, 3, 4]}

Affiliation

^[1] Univ Sao Paulo, Gen Hosp, Phys & Rehabil Med Inst, Med Sch, Sao Paulo - Brazil

^[2] Harvard Med Sch, Massachusetts Gen Hosp, Boston, MA 02115 - USA

^[3] Spaulding Rehabil Hosp, Neuromodulat Ctr, Boston, MA - USA

^[4] Spaulding Rehabil Hosp, Ctr Clin Res Learning, Boston, MA - USA

^[5] Univ San Ignacio de Loyola, Vicerrectorado Invest, Unidad Invest Generac & Sintesis Evidencias Salud, Lima - Peru

• Document type: Journal article
• Source: CLINICAL NEUROPHYSIOLOGY; v. 131, n. 8, p. 1806-1814, AUG 2020.
• Web of Science Citations: 0

Abstract

Objective: The gait recovery in spinal cord injury (SCI) seems to be partially related to the reorganization of cerebral function; however, the neural mechanisms and the respective biomarkers are not well known. This study tested the hypothesis that enhanced beta-band oscillations may be a marker of compensatory neural plasticity during the recovery period in SCI. We tested this hypothesis at baseline in SCI subjects and also in response to cortical stimulation with transcranial direct current stimulation (tDCS) combined with robotic-assisted gait training (RAGT). Methods: In this neurophysiological analysis of a randomized controlled trial, thirty-nine patients with incomplete SCI were included. They received 30 sessions of either active or sham anodal tDCS over the primary motor area for 20 min combined with RAGT. We analyzed the Electroencephalography (EEG) power spectrum and task-related power modulation of EEG oscillations, and their association with gait function indexed by Walk Index for Spinal Cord Injury (WISCI-II). Univariate and multivariate linear/logistic regression analyses were performed to identify the predictors of gait function and recovery. Results: Consistent with our hypothesis, we found that in the sensorimotor area: (1) Anodal tDCS combined with RAGT can modulate high-beta EEG oscillations power and enhance gait recovery; (2) higher high-beta EEG oscillations power at baseline can predict baseline gait function; (3) high-beta EEG oscillations power at baseline can predict gait recovery - the higher power at baseline, the better gait recovery; (4) decreases in relative high-beta power and increases in beta power decrease during walking are associated with gait recovery. Conclusions: Enhanced EEG beta oscillations in the sensorimotor area in SCI subjects may be part of a compensatory mechanism to enhance local plasticity. Our results point to the direction that interventions enhancing local plasticity such as tDCS combined with robotic training also lead to an immediate increase in sensorimotor cortex activation, improvement in gait recovery, and subsequent decrease in high-beta power. These findings suggest that beta-band oscillations may be potential biomarkers of gait function and recovery in SCI. Significance: These findings are significant for rehabilitation in SCI patients, and as EEG is a portable, inexpensive, and easy-to-apply system, the clinical translation is feasible to follow better the recovery process and to help to individualize rehabilitation therapies of SCI patients. (C) 2020 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved. (AU)

• FAPESP's process: 17/12943-8 - Inhibitory deficit as a marker of neuroplasticity in rehabilitation
• Grantee: Felipe Fregni
• Support Opportunities: Research Projects - SPEC Program