@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{MulhernBialonskiKantz2015, author = {Mulhern, Colm and Bialonski, Stephan and Kantz, Holger}, title = {Extreme events due to localization of energy}, series = {Physical Review E}, volume = {91}, journal = {Physical Review E}, number = {1}, issn = {2470-0053}, doi = {10.1103/PhysRevE.91.012918}, pages = {012918}, year = {2015}, language = {en} } @inproceedings{BornheimGriegerBialonski2021, author = {Bornheim, Tobias and Grieger, Niklas and Bialonski, Stephan}, title = {FHAC at GermEval 2021: Identifying German toxic, engaging, and fact-claiming comments with ensemble learning}, series = {Proceedings of the GermEval 2021 Workshop on the Identification of Toxic, Engaging, and Fact-Claiming Comments : 17th Conference on Natural Language Processing KONVENS 2021}, booktitle = {Proceedings of the GermEval 2021 Workshop on the Identification of Toxic, Engaging, and Fact-Claiming Comments : 17th Conference on Natural Language Processing KONVENS 2021}, publisher = {Heinrich Heine University}, address = {D{\"u}sseldorf}, doi = {10.48415/2021/fhw5-x128}, pages = {105 -- 111}, year = {2021}, language = {en} } @article{BialonskiHorstmannLehnertz2010, author = {Bialonski, Stephan and Horstmann, Marie-Therese and Lehnertz, Klaus}, title = {From brain to earth and climate systems: Small-world interaction networks or not?}, series = {Chaos: An Interdisciplinary Journal of Nonlinear Science}, volume = {20}, journal = {Chaos: An Interdisciplinary Journal of Nonlinear Science}, number = {1}, publisher = {AIP Publishing}, address = {Melville, NY}, issn = {1089-7682}, doi = {10.1063/1.3360561}, pages = {013134}, year = {2010}, abstract = {We consider recent reports on small-world topologies of interaction networks derived from the dynamics of spatially extended systems that are investigated in diverse scientific fields such as neurosciences, geophysics, or meteorology. With numerical simulations that mimic typical experimental situations, we have identified an important constraint when characterizing such networks: indications of a small-world topology can be expected solely due to the spatial sampling of the system along with the commonly used time series analysis based approaches to network characterization.}, language = {en} } @incollection{BialonskiLehnertz2013, author = {Bialonski, Stephan and Lehnertz, Klaus}, title = {From time series to complex networks: an overview}, series = {Recent Advances in Predicting and Preventing Epileptic Seizures: Proceedings of the 5th International Workshop on Seizure Prediction}, booktitle = {Recent Advances in Predicting and Preventing Epileptic Seizures: Proceedings of the 5th International Workshop on Seizure Prediction}, isbn = {978-981-4525-36-7}, doi = {10.1142/9789814525350_0010}, pages = {132 -- 147}, year = {2013}, abstract = {The network approach towards the analysis of the dynamics of complex systems has been successfully applied in a multitude of studies in the neurosciences and has yielded fascinating insights. With this approach, a complex system is considered to be composed of different constituents which interact with each other. Interaction structures can be compactly represented in interaction networks. In this contribution, we present a brief overview about how interaction networks are derived from multivariate time series, about basic network characteristics, and about challenges associated with this analysis approach.}, 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{BialonskiLehnertz2006, author = {Bialonski, Stephan and Lehnertz, Klaus}, title = {Identifying phase synchronization clusters in spatially extended dynamical systems}, series = {Physical Review E}, volume = {74}, journal = {Physical Review E}, number = {5}, issn = {2470-0053}, doi = {10.1103/PhysRevE.74.051909}, pages = {051909}, year = {2006}, language = {en} } @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} } @book{Bialonski2012, author = {Bialonski, Stephan}, title = {Inferring complex networks from time series of dynamical systems: Pitfalls, misinterpretations, and possible solutions}, publisher = {Universit{\"a}ts- und Landesbibliothek Bonn}, address = {Bonn}, pages = {Online-Ausgabe (III, 135 S. : Ill., graph. Darst.)}, year = {2012}, language = {en} } @article{BialonskiWellmerElgeretal.2006, author = {Bialonski, Stephan and Wellmer, J{\"o}rg and Elger, Christian E. and Lehnertz, Klaus}, title = {Interictal focus localization in neocortical lesional epilepsies with synchronization cluster analysis}, series = {Epilepsia}, volume = {47}, journal = {Epilepsia}, issn = {0013-9580}, pages = {36}, year = {2006}, language = {en} }