Functional restoration by brain machine interfaces based on the cortical network

为了实现更精细的基于BMI的运动控制，我们研究了基于大脑网络的解码方法，该大脑网络不仅包括初级运动皮层，还包括更高的关联区域。想象一致性分析揭示了初级运动皮层和运动前皮层、顶叶联合皮层和对侧初级运动皮层之间的功能连接可能是解码改善BMI表现的一个很好的参数。

We investigated decoding methods based on the brain network including not only the primary motor cortex but also higher associated areas in order to realize finer BMI-based motor control. Imaginary coherence analyses reveled that functional connectivity between the primary motor cortex and the premotor cortex, the parietal association cortex and the contralateral primary motor cortex may be a good parameter for decoding to improve the performance of BMIs.