Abstract

This study applied a comprehensive electroencephalography (EEG) analysis for movement-related cortical potentials (MRCPs) and event-related desynchronization (ERD) in order to understand movement-related brain activity changes during movement preparation and execution stage of unilateral wrist extension. Thirty-four healthy subjects completed two event-related potential tests in the same sequence. Unilateral wrist extension was involved in both tests as the movement task. Instruction Response Movement (IRM) was a brisk movement response task with visual “go” signal, while Cued Instruction Response Movement (CIRM) added a visual cue contenting the direction information to create a prolonged motor preparation stage. Recorded EEG data were segmented and averaged to show time domain changes and then transformed into time-frequency mapping to show the time-frequency changes. All components were calculated and compared among C3, Cz, and C4 locations. The motor potential appeared bilaterally in both tests' movement execution stages, and Cz had the largest peak value among the investigated locations (p < 0.01). In CIRM, a contingent negative variation (CNV) component presented bilaterally during the movement preparation stage with the largest amplitude at Cz. ERD of the mu rhythm (mu ERD) presented bilateral sensorimotor cortices during movement execution stages in both tests and was the smallest at Cz among the investigated locations. In the movement preparation stage of CIRM, mu ERD presented mainly in the contralateral sensory motor cortex area (C3 and C4 for right and left wrist movements, respectively) and showed significant differences between different locations. EEG changes in the time and time-frequency domains showed different topographical features. Movement execution was controlled bilaterally, while movement preparation was controlled mainly by contralateral sensorimotor cortices. Mu ERD was found to have stronger contra-lateralization features in the movement preparation stage and might be a better indicator for detecting movement intentions. This information could be helpful and might provide comprehensive information for studying movement disorders (such as those in post-stroke hemiplegic patients) or for facilitating the development of neuro-rehabilitation engineering technology such as brain computer interface.

Highlights

  • Stroke is one of the most important diseases that threatens human lives and commonly leads to motor impairments in stroke survivors [1]

  • Movement-related cortical potentials (MRCPs) and event-related desynchronization/synchronization (ERD/ERS) represent brain activity changes related to movement in the time and time-frequency domains, respectively

  • The amplitude of the negativity of MRCPs may relate to the amount of energy required for the movement, while the MRCPs’ onset time is interpreted as the length of time taken to plan and prepare the movement [19]

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Summary

Introduction

Stroke is one of the most important diseases that threatens human lives and commonly leads to motor impairments in stroke survivors [1]. Electroencephalograph (EEG)-based electrophysiological technology has been applied in the stroke research area [2,3,4,5,6,7] in addition to the rehabilitative treatment areas such as motor imagery (MI) and brain computer interface (BCI) [8,9,10,11,12,13] The aim of this preliminary study was to investigate the different features of movement-related brain activity changes during both motor intentions and motor execution in healthy people, facilitating the EEG-based investigational tool in future stroke rehabilitative studies. Delayed onset of mu ERD to movement preparation was observed consistently in patients with Parkinson’s disease, and patients with somatosensory deficits after stroke showed reduced mu ERD during both movement preparation and actual performance [4, 5] These EEG-based results enhanced the understanding of the mechanisms underlying human movement disorders [14]. Due to different protocol designs of each study and the small sample size of these studies, more studies combining temporary and oscillatory EEG data to analyze movement-related brain activity changes are necessary for understanding the whole picture of brain motor function

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