Department of Biomedical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China.
Electronic Information Department, Nanjing University of Aeronautics and Astronautics, Nanjing, China.
Brain Res. 2022 Feb 15;1777:147769. doi: 10.1016/j.brainres.2021.147769. Epub 2021 Dec 28.
Brain-computer interface (BCI) has been widely used in sports training and rehabilitation training. It is primarily based on action simulation, including movement imagery (MI) and movement observation (MO). However, the development of BCI technology is limited due to the challenge of getting an in-depth understanding of brain networks involved in MI, MO, and movement execution (ME). To better understand the brain activity changes and the communications across various brain regions under MO, ME, and MI, this study conducted the fist experiment under MO, ME, and MI. We recorded 64-channel electroencephalography (EEG) from 39 healthy subjects (25 males, 14 females, all right-handed) during fist tasks, obtained intensities and locations of sources using EEG source imaging (ESI), computed source activation modes, and finally investigated the brain networks using spectral Granger causality (GC). The brain regions involved in the three motor conditions are similar, but the degree of participation of each brain region and the network connections among the brain regions are different. MO, ME, and MI did not recruit shared brain connectivity networks. In addition, both source activation modes and brain network connectivity had lateralization advantages.
脑机接口(BCI)已广泛应用于运动训练和康复训练中。它主要基于动作模拟,包括运动想象(MI)和运动观察(MO)。然而,由于深入了解 MI、MO 和运动执行(ME)所涉及的脑网络存在挑战,BCI 技术的发展受到限制。为了更好地理解 MO、ME 和 MI 下的大脑活动变化和不同脑区之间的通讯,本研究首次在 MO、ME 和 MI 下进行了实验。我们记录了 39 名健康受试者(25 名男性,14 名女性,均为右利手)在握拳任务期间的 64 通道脑电图(EEG),使用 EEG 源成像(ESI)获得源的强度和位置,计算源激活模式,最后使用频谱 Granger 因果关系(GC)研究大脑网络。三个运动条件涉及的大脑区域相似,但每个大脑区域的参与程度和大脑区域之间的网络连接不同。MO、ME 和 MI 没有招募共享的大脑连通性网络。此外,源激活模式和脑网络连接都具有优势。