Correia Pedro, Quintão Carla, Quaresma Cláudia, Vigário Ricardo
Physics Department, NOVA School of Science and Technology, NOVA University of Lisbon, 2829-516 Caparica, Portugal.
Laboratory of Instrumentation, Biomedical Engineering and Radiation Physics (LIBPhys-UNL), NOVA School of Science and Technology, NOVA University of Lisbon, 2829-516 Caparica, Portugal.
Methods Protoc. 2025 Jul 7;8(4):74. doi: 10.3390/mps8040074.
Sophisticated voluntary movements are essential for everyday functioning, making the study of how the brain controls muscle activity a central challenge in neuroscience. Investigating corticomuscular control through non-invasive electrophysiological recordings is particularly complex due to the intricate nature of neuronal signals. To address this challenge, we present a novel experimental methodology designed to study corticomuscular control using electroencephalography (EEG) and electromyography (EMG). Our approach integrates a serious gaming biofeedback system with a specialized experimental protocol for simultaneous EEG-EMG data acquisition, optimized for corticomuscular studies. This work introduces, for the first time, a method for assessing brain-muscle functional connectivity during the execution of a demanding motor task. By identifying neuronal sources linked to muscular activity, this methodology has the potential to advance our understanding of motor control mechanisms. These insights could contribute to improving clinical practices and fostering the development of novel brain-computer interface technologies.
复杂的自主运动对日常功能至关重要，这使得研究大脑如何控制肌肉活动成为神经科学的核心挑战。由于神经元信号的复杂性，通过非侵入性电生理记录来研究皮质肌肉控制尤为复杂。为应对这一挑战，我们提出了一种新颖的实验方法，旨在利用脑电图（EEG）和肌电图（EMG）来研究皮质肌肉控制。我们的方法将一个严肃游戏生物反馈系统与一个专门的实验方案相结合，用于同步采集EEG-EMG数据，该方案针对皮质肌肉研究进行了优化。这项工作首次介绍了一种在执行具有挑战性的运动任务期间评估脑-肌肉功能连接性的方法。通过识别与肌肉活动相关的神经元来源，这种方法有潜力增进我们对运动控制机制的理解。这些见解可能有助于改善临床实践并促进新型脑机接口技术的发展。
