Beta-band oscillations as a biomarker of gait recovery in spinal cord injury patients: A quantitative electroencephalography analysis.
Adolescent
Adult
Beta Rhythm
/ physiology
Electroencephalography
Female
Gait
/ physiology
Humans
Male
Middle Aged
Motor Cortex
/ physiopathology
Recovery of Function
/ physiology
Spinal Cord Injuries
/ physiopathology
Transcranial Direct Current Stimulation
/ methods
Treatment Outcome
Walking
/ physiology
Young Adult
Electroencephalography
Gait function
Power analysis
Predictors
Spinal cord injury
Task-related power modulation
Journal
Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
ISSN: 1872-8952
Titre abrégé: Clin Neurophysiol
Pays: Netherlands
ID NLM: 100883319
Informations de publication
Date de publication:
08 2020
08 2020
Historique:
received:
22
11
2019
revised:
26
03
2020
accepted:
09
04
2020
pubmed:
17
6
2020
medline:
25
5
2021
entrez:
17
6
2020
Statut:
ppublish
Résumé
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). 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. 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. 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. 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.
Identifiants
pubmed: 32540720
pii: S1388-2457(20)30328-X
doi: 10.1016/j.clinph.2020.04.166
pii:
doi:
Types de publication
Journal Article
Randomized Controlled Trial
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1806-1814Informations de copyright
Copyright © 2020 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of Competing Interest None of the authors have potential conflicts of interest to be disclosed.