Evolving networks in the human epileptic brain

PHYSICA D-NONLINEAR PHENOMENA

卷:267

Article

Lehnertz, Klaus^1,2,3  Ansmann, Gerrit^1,2,3  Bialonski, Stephan^1,2,3  Dickten, Henning^1,2,3  Geier, Christian^1,2  Porz, Stephan^1,2 

[1] Univ Bonn, Dept Epileptol, D-53105 Bonn, Germany

[2] Univ Bonn, Helmholtz Inst Radiat & Nucl Phys, D-53115 Bonn, Germany

[3] Univ Bonn, Interdisciplinary Ctr Complex Syst, D-53175 Bonn, Germany

关键词: Complex networks;    Epileptic brain networks;    Network inference;    Network characteristics;    Neural activity;    Time series analysis;   

DOI  :  10.1016/j.physd.2013.06.009

来源: Elsevier

【 摘 要 】

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.

【 授权许可】

Free