一种动态系统方法来描述运动期间的大脑与身体的相互作用:挑战,解释和建议
Derek C Monroe1, Nathaniel T Berry1,2, Peter C Fino3
1Department of Kinesiology, University of North Carolina at Greensboro, Greensboro, NC 27402, USA.
Sensors (Basel, Switzerland)
|July 29, 2023
概括
本综述提供了一个关于使用动态系统研究脑体相互作用 (BBIs) 的教程. 它解决了解释脑电图 (EEG) 和神经康复和运动控制研究的动力学数据的局限性.
科学领域:
- 神经科学是一个神经科学.
- 生物物理学的生物物理.
- 机器人技术 机器人技术 机器人技术
背景情况:
- 大脑与身体的相互作用 (BBIs) 是理解运动控制的核心.
- 目前的BBI研究往往从行为上解释大脑活动,而不是从神经解剖学或生物物理上解释.
- 现有的研究BBI的方法与动态系统方法不一致.
研究的目的:
- 为通过动态系统镜头研究BBIs提供一个教程.
- 为了解决当前BBI研究方法的局限性.
- 引导研究人员进行神经成像和神经康复.
主要方法:
- 概述了在全身运动期间获取,解释和清理脑电图 (EEG) 的最佳实践.
- 讨论模拟EEG和动力学数据作为动态系统的理论.
- 展示使用模型系统和从步行任务中获得的经验数据的工作示例.
主要成果:
- 使用动态系统分析脑体相互作用的框架.
- 展示了使用EEG和动力学数据的方法的实际应用.
- 突出显示了运动期间神经活动的改进解释.
结论:
- 克服BBI研究的方法限制对于推进神经成像和神经康复至关重要.
- 动态系统方法为理解神经运动控制提供了更强大的框架.
- 这个教程为研究人员提供了工具,以更好地研究大脑与身体的协调.
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