Liu Yuan, Huang Shuaifei, Xu Weiguo, Wang Zhuang, Ming Dong
Academy of Medical Engineering and Translational Medicine (AMT), Tianjin University, Tianjin, China.
Haihe Laboratory of Brain-Computer Interaction and Human-Machine Integration, Tianjin, Tianjin, China.
NPJ Sci Learn. 2024 Dec 30;9(1):80. doi: 10.1038/s41539-024-00294-y.
Generalization is central to motor learning. However, few studies are on the learning generalization of BCI-actuated supernumerary robotic finger (BCI-SRF) for human-machine interaction training, and no studies have explored its longitudinal neuroplasticity mechanisms. Here, 20 healthy right-handed participants were recruited and randomly assigned to BCI-SRF group or inborn finger group (Finger) for 4-week training and measured by novel SRF-finger opposition sequences and multimodal MRI. After training, the BCI-SRF group showed 350% times compared to the Finger group in the improvement of sequence opposition accuracy before and after training, and accompanied by significant functional connectivity increases in the sensorimotor region and prefrontal cortex, as well as in the intra- and inter-hemisphere of the sensorimotor network. Moreover, Granger Causality Analysis identified causal effect main transfer within the sensorimotor cortex-cerebellar-thalamus loop and frontal-parietal loop. The findings suggest that BCI-SRF training enhances motor sequence learning ability by influencing the functional reorganization of sensorimotor network.
泛化是运动学习的核心。然而,针对用于人机交互训练的脑机接口驱动的多指机器人手指(BCI-SRF)的学习泛化的研究很少,并且没有研究探索其纵向神经可塑性机制。在此,招募了20名健康的右利手参与者,并将他们随机分配到BCI-SRF组或固有手指组(手指组)进行为期4周的训练,并通过新颖的SRF-手指对指序列和多模态MRI进行测量。训练后,与手指组相比,BCI-SRF组在训练前后序列对指准确性的提高上表现出350%的提升,同时感觉运动区域和前额叶皮层以及感觉运动网络半球内和半球间的功能连接显著增加。此外,格兰杰因果分析确定了感觉运动皮层-小脑-丘脑环路和额顶叶环路内的因果效应主要传递。研究结果表明,BCI-SRF训练通过影响感觉运动网络的功能重组来增强运动序列学习能力。