Functional restoration by brain machine interfaces based on the cortical network

我们研究了基于大脑网络的解码方法，不仅包括初级运动皮质，还包括高级关联区域，以实现更精细的基于BMI的运动控制。想象连贯性分析表明，初级运动皮质和运动前皮质、顶叶联合皮质和对侧初级运动皮质之间的功能连接可能是解码以提高BMI成绩的一个很好的参数。

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.