基于图论算法的脊髓损伤后大脑皮层运动区神经元网络分析

 脊髓损伤(SCI)后大脑皮层运动区神经元的功能重组对机体功能康复的影响仍然不为人知。脊髓损伤前后，对一只在跑步机上直立行走的恒河猴的大脑皮层运动区神经元信号进行记录，利用不同神经元动作电位序列间的相关系数建立神经元网络图。为了研究神经元活动模式的变化与功能康复之间的联系，利用图论算法计算了神经元网络图的全局效能指标和神经元脆弱性指标。结果显示，不同时期神经元活动模式的显著变化意味着运动区神经元的功能重组(神经可塑性)与脊髓损伤后猴子的功能康复状态紧密相关，且这种神经功能重组对于猴子步行功能的康复起了非常重要的积极作用。

Graph Analysis for the Motor Cortical Neuron Network Post Spinal Cord Injury

The impact of the potential functional reorganization in neuronal populations in motor cortical areas during the functional recovery post a Spinal Cord Injury (SCI) remains unclear. In this study, the cortical neuronal data were recorded from a monkey while it was trained to walk bipedally on a treadmill both before and after the spinal cord injury. A neuronal network graph for multiple steps in different sessions was constructed by using the correlation coefficients between different neurons. The global efficiency and the vulnerability of the graph were then evaluated to reveal the intrinsic relation between the changes of the neuronal activity patterns and the functional recovery. The preliminary results indicate that the observed significant changes in the neuronal activity patterns in the motor cortex suggest that the patterns of the functional reorganization (neural plasticity) in the motor areas of the cortex are correlated and they make contributions to the functional recovery.