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首页> 外文期刊>Philosophical Transactions of the Royal Society of London, Series B. Biological Sciences >Graph analysis of functional brain networks: practical issues in translational neuroscience
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Graph analysis of functional brain networks: practical issues in translational neuroscience

机译:功能脑网络图分析:转化神经科学中的实际问题

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摘要

The brain can be regarded as a network: a connected system where nodes, or units, represent different specialized regions and links, or connections, represent communication pathways. From a functional perspective, communication is coded by temporal dependence between the activities of different brain areas. In the last decade, the abstract representation of the brain as a graph has allowed to visualize functional brain networks and describe their non-trivial topological properties in a compact and objectiveway.Nowadays, the use of graph analysis in translational neuroscience has become essential to quantify brain dysfunctions in terms of aberrant reconfiguration of functional brain networks. Despite its evident impact, graph analysis of functional brain networks is not a simple toolbox that can be blindly applied to brain signals. On the one hand, it requires the know-how of all the methodological steps of the pipeline that manipulate the input brain signals and extract the functional network properties. On the other hand, knowledge of the neural phenomenon under study is required to perform physiologically relevant analysis. The aim of this review is to provide practical indications to make sense of brain network analysis and contrast counterproductive attitudes.
机译:大脑可以看作是一个网络:一个连接的系统,其中的节点或单元代表不同的专用区域,而链接或连接则代表通信路径。从功能的角度来看,交流是通过不同大脑区域活动之间的时间依赖性进行编码的。在过去的十年中,大脑以图形的抽象表示使可视化的功能性大脑网络可视化并以紧凑,客观的方式描述其非平凡的拓扑特性。如今,在转化神经科学中使用图形分析已成为量化量化的必要条件从功能性大脑网络的异常重新配置方面来看,大脑功能障碍。尽管有明显的影响,但是功能大脑网络的图形分析并不是一个可以盲目地应用于大脑信号的简单工具箱。一方面,它需要管道的所有方法步骤的知识,这些方法可以操纵输入的大脑信号并提取功能网络属性。另一方面,需要进行研究中的神经现象的知识以进行生理上相关的分析。这篇综述的目的是提供有用的适应症,以使人对大脑网络进行分析并对比适得其反的态度。

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