Lei X, Huang B, Li H, Jiang H, Hu X, Zhang B
Department of Neurology, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310009, China.
Key Laboratory of Animal Models and Human Disease Mechanisms of Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Kunming, Yunnan 650223, China; University of the Chinese Academy of Sciences, Beijing 100049, China.
Neuroscience. 2015 Jul 23;299:107-24. doi: 10.1016/j.neuroscience.2015.04.056. Epub 2015 Apr 30.
Understanding the role of brain regions in anatomical neural networks with Parkinson's disease (PD) is essential for improving the clinical protocol or finding new targets for deep brain stimulation (DBS). Although numerous changes have been reported in local functional studies, few studies have reported on the anatomical network of the entire brain. Here, by developing a series of algorithms, this study provided a whole anatomical neural network of the macaque monkey. Then, the drifts in centrality from normal to PD networks were described in terms of complex network analysis and summarized with principal component analysis. Results revealed that the areas including the striatum, globus pallidus, amygdala, prefrontal lobe, thalamus, hippocampus, visual cortex, insula, etc., showed relatively notable drifts in their own patterns. The present study also demonstrated that the current targets of DBS shared a common feature: their centrality values being relatively low in the normal brain while intensely drifting with PD.
了解帕金森病（PD）患者大脑区域在解剖神经网络中的作用对于改进临床方案或寻找深部脑刺激（DBS）的新靶点至关重要。尽管在局部功能研究中已报道了许多变化，但很少有研究报道整个大脑的解剖网络。在此，通过开发一系列算法，本研究提供了猕猴的全脑解剖神经网络。然后，通过复杂网络分析描述了从正常网络到PD网络的中心性漂移，并通过主成分分析进行了总结。结果显示，包括纹状体、苍白球、杏仁核、前额叶、丘脑、海马体、视觉皮层、岛叶等区域，在其自身模式上表现出相对明显的漂移。本研究还表明，当前DBS的靶点具有一个共同特征：它们在正常大脑中的中心性值相对较低，而在PD时急剧漂移。
