SUISHI (Tianjin) Intelligence Ltd, China; Haihe Laboratory of Brain-computer Interaction and Human-machine Integration, Tianjin, China.
Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China; Haihe Laboratory of Brain-computer Interaction and Human-machine Integration, Tianjin, China.
Neuroscience. 2023 Oct 15;530:56-65. doi: 10.1016/j.neuroscience.2023.08.032. Epub 2023 Aug 29.
Motor imagery based brain-computer interfaces (MI-BCIs) have excellent application prospects in motor enhancement and rehabilitation. However, MI-induced electroencephalogram features applied to MI-BCI usually vary from person to person. This study aimed to investigate whether the motor ability of the individual upper limbs was associated with these features, which helps understand the causes of inter-subject variability. We focused on the behavioral and psychological factors reflecting motor abilities. We first obtained the behavioral scale scores from Edinburgh Handedness Questionnaire, Maximum Grip Strength Test, and Purdue Pegboard Test assessments to evaluate the motor execution ability. We also required the subjects to complete the psychological Movement Imagery Questionnaire-3 estimate, representing MI ability. Then we recorded EEG signals from all twenty-two subjects during MI tasks. Pearson correlation coefficient and stepwise regression were used to analyze the relationships between MI-induced relative event-related desynchronization (rERD) patterns and motor abilities. Both Purdue Pegboard Test and Movement Imagery Questionnaire-3 scores had significant correlations with MI-induced neural oscillation patterns. Notably, the Purdue Pegboard Test of the left hand had the most significant correlation with the alpha rERD. The results of stepwise multiple regression analysis showed that the Purdue Pegboard Test and Movement Imagery Questionnaire-3 could best predict the MI-induced rERD. The results demonstrate that hand dexterity and fine motor coordination are significantly related to MI-induced neural activities. In addition, the method of imagining is also relevant to MI features. Therefore, this study is meaningful for understanding individual differences and the design of user-centered MI-BCI.
基于运动想象的脑-机接口(MI-BCI)在运动增强和康复方面具有广阔的应用前景。然而,应用于 MI-BCI 的 MI 诱发脑电特征通常因人而异。本研究旨在探讨个体上肢的运动能力是否与这些特征相关,这有助于理解受试者间变异性的原因。我们重点关注反映运动能力的行为和心理因素。我们首先从 Edinburgh 手性问卷、最大握力测试和 Purdue 钉板测试评估中获得行为量表得分,以评估运动执行能力。我们还要求受试者完成运动想象问卷-3 估计,以代表 MI 能力。然后,我们在所有 22 名受试者进行 MI 任务时记录 EEG 信号。使用 Pearson 相关系数和逐步回归分析 MI 诱导的相对事件相关去同步(rERD)模式与运动能力之间的关系。Purdue 钉板测试和运动想象问卷-3 得分均与 MI 诱导的神经振荡模式显著相关。值得注意的是,左手的 Purdue 钉板测试与 alpha rERD 相关性最强。逐步多元回归分析的结果表明,Purdue 钉板测试和运动想象问卷-3 可以最好地预测 MI 诱导的 rERD。结果表明,手的灵巧度和精细运动协调能力与 MI 诱导的神经活动显著相关。此外,想象的方法也与 MI 特征有关。因此,本研究对于理解个体差异和设计以用户为中心的 MI-BCI 具有重要意义。