@article{LehnertzAnsmannBialonskietal.2014,
  author    = {Lehnertz, Klaus and Ansmann, Gerrit and Bialonski, Stephan and Dickten, Henning and Geier, Christian and Porz, Stephan},
  title     = {Evolving networks in the human epileptic brain},
  series = {Physica D: Nonlinear Phenomena},
  volume    = {267},
  journal   = {Physica D: Nonlinear Phenomena},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {0167-2789},
  doi       = {10.1016/j.physd.2013.06.009},
  pages     = {7 -- 15},
  year      = {2014},
  abstract  = {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.},
  language  = {en}
}
@article{GeierLehnertzBialonski2015,
  author    = {Geier, Christian and Lehnertz, Klaus and Bialonski, Stephan},
  title     = {Time-dependent degree-degree correlations in epileptic brain networks: from assortative to dissortative mixing},
  series = {Frontiers in Human Neuroscience},
  journal   = {Frontiers in Human Neuroscience},
  publisher = {Frontiers Research Foundation},
  address   = {Lausanne},
  issn      = {1662-5161},
  doi       = {10.3389/fnhum.2015.00462},
  year      = {2015},
  language  = {en}
}
@article{GeierBialonskiElgeretal.2015,
  author    = {Geier, Christian and Bialonski, Stephan and Elger, Christian E. and Lehnertz, Klaus},
  title     = {How important is the seizure onset zone for seizure dynamics?},
  series = {Seizure},
  volume    = {25},
  journal   = {Seizure},
  issn      = {1059-1311},
  doi       = {10.1016/j.seizure.2014.10.013},
  pages     = {160 -- 166},
  year      = {2015},
  language  = {en}
}
@article{NgamgaBialonskiMarwanetal.2016,
  author    = {Ngamga, Eulalie Joelle and Bialonski, Stephan and Marwan, Norbert and Kurths, J{\"u}rgen and Geier, Christian and Lehnertz, Klaus},
  title     = {Evaluation of selected recurrence measures in discriminating pre-ictal and inter-ictal periods from epileptic EEG data},
  series = {Physics Letters A},
  volume    = {380},
  journal   = {Physics Letters A},
  number    = {16},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {0375-9601},
  doi       = {10.1016/j.physleta.2016.02.024},
  pages     = {1419 -- 1425},
  year      = {2016},
  abstract  = {We investigate the suitability of selected measures of complexity based on recurrence quantification analysis and recurrence networks for an identification of pre-seizure states in multi-day, multi-channel, invasive electroencephalographic recordings from five epilepsy patients. We employ several statistical techniques to avoid spurious findings due to various influencing factors and due to multiple comparisons and observe precursory structures in three patients. Our findings indicate a high congruence among measures in identifying seizure precursors and emphasize the current notion of seizure generation in large-scale epileptic networks. A final judgment of the suitability for field studies, however, requires evaluation on a larger database.},
  language  = {en}
}