Evolving networks in the human epileptic brain
Evolving networks in the human epileptic brain
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DOI：
10.1016/j.physd.2013.06.009
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发表时间：
2014-01-15
影响因子：
4
通讯作者：
Porz, Stephan
中科院分区：
文献类型：
--
作者：
Lehnertz, Klaus;Ansmann, Gerrit;Porz, Stephan
网络理论提供了新的概念，有望改善相互作用的动力系统的特征。在这个框架内，演化的网络可以被认为是由节点组成的，表示系统，以及由时变的边组成的，表示这些系统之间的交互。这一方法对于进一步了解人脑网络中的生理和病理生理动力学具有很大的吸引力。的确，越来越多的证据表明，癫痫过程可以被视为一种大规模的网络现象。我们在这里回顾了从经验时间序列推断网络以及描述这些不断演变的网络的方法。我们总结了最近的研究结果，这些研究调查了人类癫痫脑网络在几秒钟到几周的时间尺度上的演变。我们指出了可能的陷阱和有待解决的问题，并讨论了未来的前景。(C)2013爱思唯尔B.V.保留所有权利。
Network theory provides novel concepts that promise an improved characterization of interacting dynamical systems. Within this framework, evolving networks can be considered as being composed of nodes, representing systems, and of time-varying edges, representing interactions between these systems. This approach is highly attractive to further our understanding of the physiological and pathophysiological dynamics in human brain networks. Indeed, there is growing evidence that the epileptic process can be regarded as a large-scale network phenomenon. We here review methodologies for inferring networks from empirical time series and for a characterization of these evolving networks. We summarize recent findings derived from studies that investigate human epileptic brain networks evolving on timescales ranging from few seconds to weeks. We point to possible pitfalls and open issues, and discuss future perspectives. (C) 2013 Elsevier B.V. All rights reserved.