@article{KuhnertBialonskiNoenningetal.2013,
  author    = {Kuhnert, Marie-Therese and Bialonski, Stephan and Noenning, Nina and Mai, Heinke and Hinrichs, Hermann and Helmstaedter, Christoph and Lehnertz, Klaus},
  title     = {Incidental and intentional learning of verbal episodic material differentially modifies functional brain networks},
  series = {Plos one},
  volume    = {8},
  journal   = {Plos one},
  number    = {11},
  publisher = {PLOS},
  address   = {San Francisco},
  doi       = {10.1371/journal.pone.0080273},
  pages     = {e80273},
  year      = {2013},
  abstract  = {Learning- and memory-related processes are thought to result from dynamic interactions in large-scale brain networks that include lateral and mesial structures of the temporal lobes. We investigate the impact of incidental and intentional learning of verbal episodic material on functional brain networks that we derive from scalp-EEG recorded continuously from 33 subjects during a neuropsychological test schedule. Analyzing the networks' global statistical properties we observe that intentional but not incidental learning leads to a significantly increased clustering coefficient, and the average shortest path length remains unaffected. Moreover, network modifications correlate with subsequent recall performance: the more pronounced the modifications of the clustering coefficient, the higher the recall performance. Our findings provide novel insights into the relationship between topological aspects of functional brain networks and higher cognitive functions.},
  language  = {en}
}
@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}
}
@incollection{LehnertzBialonskiHorstmannetal.2010,
  author    = {Lehnertz, Klaus and Bialonski, Stephan and Horstmann, Marie-Therese and Krug, Dieter and Rothkegel, Alexander and Staniek, Matth{\"a}us and Wagner, Tobias},
  title     = {Epilepsy},
  series = {Reviews of Nonlinear Dynamics and Complexity, Volume 2},
  booktitle = {Reviews of Nonlinear Dynamics and Complexity, Volume 2},
  publisher = {Wiley-VCH},
  isbn      = {9783527628001},
  doi       = {10.1002/9783527628001.ch5},
  pages     = {159 -- 200},
  year      = {2010},
  language  = {en}
}
@article{LehnertzBialonskiHorstmannetal.2009,
  author    = {Lehnertz, Klaus and Bialonski, Stephan and Horstmann, Marie-Therese and Krug, Dieter and Rothkegel, Alexander and Staniek, Matth{\"a}us and Wagner, Tobias},
  title     = {Synchronization phenomena in human epileptic brain networks},
  series = {Journal of neuroscience methods},
  volume    = {183},
  journal   = {Journal of neuroscience methods},
  number    = {1},
  issn      = {0165-0270},
  doi       = {10.1016/j.jneumeth.2009.05.015},
  pages     = {42 -- 48},
  year      = {2009},
  language  = {en}
}
@article{LehnertzMormannOsterhageetal.2007,
  author    = {Lehnertz, Klaus and Mormann, Florian and Osterhage, Hannes and Andy, M{\"u}ller and Prusseit, Jens and Chernihovskyi, Anton and Staniek, Matth{\"a}us and Krug, Dieter and Bialonski, Stephan and Elger, Christian E.},
  title     = {State-of-the-art of seizure prediction},
  series = {Journal of Clinical Neurophysiology},
  volume    = {24},
  journal   = {Journal of Clinical Neurophysiology},
  number    = {2},
  issn      = {1537-1603},
  doi       = {10.1097/WNP.0b013e3180336f16},
  pages     = {147 -- 153},
  year      = {2007},
  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}
}
@incollection{OsterhageBialonskiStanieketal.2008,
  author    = {Osterhage, Hannes and Bialonski, Stephan and Staniek, Matth{\"a}us and Schindler, Kaspar and Wagner, Tobias and Elger, Christian E. and Lehnertz, Klaus},
  title     = {Bivariate and multivariate time series analysis techniques and their potential impact for seizure prediction},
  series = {Seizure Prediction in Epilepsy: From Basic Mechanisms to Clinical Applications},
  booktitle = {Seizure Prediction in Epilepsy: From Basic Mechanisms to Clinical Applications},
  publisher = {Wiley-VCH},
  address   = {Weinheim},
  isbn      = {978-3-527-62519-2},
  doi       = {10.1002/9783527625192.ch15},
  pages     = {189 -- 208},
  year      = {2008},
  language  = {en}
}
@article{SchindlerBialonskiHorstmannetal.2008,
  author    = {Schindler, Kaspar A. and Bialonski, Stephan and Horstmann, Marie-Therese and Elger, Christian E. and Lehnertz, Klaus},
  title     = {Evolving functional network properties and synchronizability during human epileptic seizures},
  series = {Chaos: An Interdisciplinary Journal of Nonlinear Science},
  volume    = {18},
  journal   = {Chaos: An Interdisciplinary Journal of Nonlinear Science},
  number    = {3},
  issn      = {1089-7682},
  doi       = {10.1063/1.2966112},
  pages     = {033119},
  year      = {2008},
  language  = {en}
}