Motor imagery EEG microstates are influenced by alpha power.

IF 1.7 4区 医学 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Xin Xiong, Xiaoyu Ji, Sanli Yi, Chunwu Wang, Ruixiang Liu, Jianfeng He
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引用次数: 0

Abstract

Electroencephalogram (EEG) microstates are pivotal in understanding brain dynamics, reflecting transitions between global states. These parameters undergo selective inhibition within cortical areas, modulated by alpha oscillations. This study investigates how alpha band power influences microstate parameters across various task conditions, including resting state, actual motor execution, and imagined motor tasks. By comparing these three conditions, we aim to elucidate the distinct effects of alpha power on microstate dynamics, as each condition represents a unique pattern of brain activity. Motor imagery (MI) induces event-related desynchronization/synchronization, modulating Mu (alpha) and Beta rhythms in sensorimotor areas. However, the relationship between MI-EEG microstates and alpha power remains unclear. Our results show that alpha power was highest in resting state, followed by imagined motion, and lowest during actual motion. As alpha power increased, microstate A parameters in resting state (occurrence, coverage) decreased, while those in actual motion increased. Additionally, microstate B parameters rose with alpha power in resting state but decreased during imagined motion. Notably, alpha power correlated more strongly with microstate parameters in task states than in resting state. In addition, alpha, theta, and beta powers during task performance were negatively correlated with the duration of microstates A, B, and C, while being positively correlated with the occurrence of microstates A, B, C, and D. These findings suggest that alpha power influences microstate parameters differently depending on the brain, underscoring the significance of inter-band interactions in shaping microstate dynamics.

运动想象的脑电图微观状态受阿尔法功率的影响。
脑电图(EEG)微观状态是理解脑动力学的关键,反映了全局状态之间的转换。这些参数在皮层区域选择性抑制,由α振荡调制。本研究探讨了α波段功率如何影响各种任务条件下的微状态参数,包括静息状态、实际运动执行和想象运动任务。通过比较这三种情况,我们的目的是阐明α功率对微观状态动力学的不同影响,因为每种情况都代表了一种独特的大脑活动模式。运动意象(MI)诱导事件相关的去同步/同步,调节感觉运动区的Mu (α)和β节律。然而,MI-EEG微观状态与α功率之间的关系尚不清楚。结果表明,静息状态下alpha功率最高,想象运动次之,而实际运动时alpha功率最低。随着alpha功率的增加,静息状态下的微态A参数(发生率、覆盖率)减少,而实际运动状态下的微态A参数增加。在静息状态下,微态B参数随α功率升高而升高,而在想象运动时则下降。值得注意的是,与静息状态相比,任务状态下α功率与微状态参数的相关性更强。此外,任务执行中的α、θ和β功率与微状态A、B和C的持续时间呈负相关,而与微状态A、B、C和d的发生呈正相关。这些发现表明α功率对微状态参数的影响因大脑而异,强调了波段间相互作用在形成微状态动力学中的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
4.10
自引率
6.20%
发文量
179
审稿时长
4-8 weeks
期刊介绍: The primary aims of Computer Methods in Biomechanics and Biomedical Engineering are to provide a means of communicating the advances being made in the areas of biomechanics and biomedical engineering and to stimulate interest in the continually emerging computer based technologies which are being applied in these multidisciplinary subjects. Computer Methods in Biomechanics and Biomedical Engineering will also provide a focus for the importance of integrating the disciplines of engineering with medical technology and clinical expertise. Such integration will have a major impact on health care in the future.
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