Electroencephalography Network Indices as Biomarkers of Upper Limb Impairment in Chronic Stroke

Summary

The experimental protocol demonstrates the paradigm for acquiring and analyzing electroencephalography (EEG) signals during upper limb movement in individuals with stroke. The alteration of the functional network of low-beta EEG frequency bands was observed during the movement of the impaired upper limb and was associated with the degree of motor impairment.

Abstract

Alteration of electroencephalography (EEG) signals during task-specific movement of the impaired limb has been reported as a potential biomarker for the severity of motor impairment and for the prediction of motor recovery in individuals with stroke. When implementing EEG experiments, detailed paradigms and well-organized experiment protocols are required to obtain robust and interpretable results. In this protocol, we illustrate a task-specific paradigm with upper limb movement and methods and techniques needed for the acquisition and analysis of EEG data. The paradigm consists of 1 min of rest followed by 10 trials comprising alternating 5 s and 3 s of resting and task (hand extension)-states, respectively, over 4 sessions. EEG signals were acquired using 32 Ag/AgCl scalp electrodes at a sampling rate of 1,000 Hz. Event-related spectral perturbation analysis associated with limb movement and functional network analyses at the global level in the low-beta (12-20 Hz) frequency band were performed. Representative results showed an alteration of the functional network of low-beta EEG frequency bands during movement of the impaired upper limb, and the altered functional network was associated with the degree of motor impairment in chronic stroke patients. The results demonstrate the feasibility of the experimental paradigm in EEG measurements during upper limb movement in individuals with stroke. Further research using this paradigm is needed to determine the potential value of EEG signals as biomarkers of motor impairment and recovery.

Introduction

Upper limb motor impairment is one of the most common consequences of stroke and is related to limitations in activities of daily living^1,2. Alpha (8-13 Hz) and beta (13-30 Hz) band rhythms are known to be closely associated with movements. In particular, studies have shown that altered neural activity in the alpha and lower beta (12-20 Hz) frequency bands during movement of an impaired limb is correlated with the degree of motor impairment in individuals with stroke^3,4,5. Based on these findings, electroencephalograp....

Protocol

All experimental procedures were reviewed and approved by the Institutional Review Board of Seoul National University Bundang Hospital. For the experiments in this study, 34 participants with stroke were recruited. Signed informed consent was obtained from all participants. A signed informed consent was obtained from a legal representative if a participant met the criteria but could not sign the consent form because of disability.

1. Experimental setup

1. Patient recr.......

Discussion

This study has introduced an EEG experiment for measuring upper limb movement-related neuronal activities in individuals with stroke. The experimental paradigm and methods of acquisition and analysis of EEG were applied to determine the ERD patterns in the ipsilesional and contralesional motor cortex.

The results of the ERSP maps (Figure 7) demonstrated the difference in the degree of neuronal activation when moving the impaired and unaffected hands. The results .......

Materials

Name	Company	Catalog Number	Comments
actiCAP	Easycap, GmbH Ltd., Herrsching, Germany	CAC-32-SAMW-56	Textile EEG cap platform to accommodate EEG electrodes
Brain Vision Recorder (Software)	Brain Products GmBH Ltd., Munich, Germany	-	Software used to record EEG signal
Curry 7 (Software)	Compumedics, Australia	-	Software used in preprocessing of EEG data
LiveAmp	Brain Products, GmbH Ltd., Gilching, Germany	LA-055606-0348	EEG system (amplifier) used for the measurement
MATLAB R2019a (Software)	MathWorks Inc., Natick, MA, USA	-	Software used to run the experimental stimulus and analyze the EEG data
Recording PC	Lenovo Group Limited, Hong Kong, China	Model: X58K	Intel Core i7-7700HQ CPU@2.80 GHz, RAM 8 GB /EEG data recording using Brain Vision Recorder
Sensor&Trigger Extension(STE)	Brain Products GmBH Ltd., Munich, Germany	STE-055604-0162	Adds physioloigcal signals to the EEG amplifier
Splitter box	Brain Products GmBH Ltd., Munich, Germany	BP-135-1600	Connects Ag/AgCl electrodes to the EEG amplifier
Stimulation PC	Hansung Corporation, Seoul, Korea	Model: ThinkPad P71	Intel Core i7-8750H CPU@2.20 GHz, RAM 8 GB Presenting stimulation screen using MATLAB
TriggerBox	Brain Products GmBH Ltd., Munich, Germany	BP-245-1010	Receives trigger signal from PC and relay it to EEG recording system